mirror of
https://github.com/personamanagmentlayer/pcl.git
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4e07a6a874
* chore(stdlib): add conformance tooling for the skills library
The library had no gate that could express what a valid skill is, so
malformed frontmatter, over-budget files and credential literals went
unnoticed. These scripts define and enforce that contract.
- validate-skills.py: extend with Agent Skills v1.0 conformance -
naming rules and directory agreement, an explicit activation trigger
in the description, canonical layout, the 500-line SKILL.md budget,
relative-link integrity, and two security rules (no unrestricted
Bash(*) grant, no credential literals). Structural checks now read a
skill as a whole so material moved into references/ still counts.
- split-skill-references.py: move the heaviest sections of an oversized
SKILL.md into references/. Verifies line by line that every source
line lands in exactly one output and refuses to write otherwise.
- generate-skill-inventory.py: derive SKILLS_INVENTORY.md and
DIRECTORY_STRUCTURE.md from the tree so they cannot drift.
- generate-skill-catalog.py: index the canonical layout only, count
references/ toward a skill's size, and stop truncating descriptions
at 200 characters - the catalog is the discovery surface and must
carry the activation trigger.
- .gitignore: Python bytecode from these scripts, and local .pcl state.
Reviewed-by: Security Analyst, Compiler Engineer, DevX Engineer
* fix(stdlib): bring all 174 skills to Agent Skills v1.0 conformance
No skill in the library was conformant. 41 of 175 failed the existing
validator outright, and none satisfied the spec. This pass fixes the
tree and records the result. See stdlib/CHANGELOG.md for the per-skill
versioning and migration notes.
BREAKING CHANGE: one skill removed, five moved, seven with a capability
withdrawn. Library version 2.0.0 -> 3.0.0.
Structure
- Convert 71 skills stored as flat files to <category>/<name>/SKILL.md,
the layout the spec requires and the only one able to carry companion
resources.
- Rename 5 directories that disagreed with their declared name:, so
resolution by path and by name stop giving different answers. The
repository docs already referenced the corrected paths.
- Merge the duplicate legal-technology skills into legaltech-expert and
delete legal-tech-expert, carrying over everything the survivor
lacked.
Metadata
- Repair 20 unparseable frontmatters: an H1 preceded the --- block and
the key was skill_id: instead of name:, so any parser reading
frontmatter at offset 0 saw no metadata at all. The objectives,
prerequisites and outcome they carried become real body sections.
- Add the missing version: to 21 skills, fold keywords into tags, move
expertise_level under metadata, and align 10 category: values with
their directory.
Discoverability
- Give all 174 descriptions an explicit "Use when ..." trigger, built
from each skill's own tags and section headings. 152 previously said
only what the skill was about, leaving an agent nothing to match on.
Progressive disclosure
- Split 127 oversized skills, moving bulk material into references/ read
on demand and leaving an index behind. A SKILL.md now averages 277
lines instead of 644 and none exceeds 500. Verified lossless line by
line against the previous revision.
Security
- Withdraw the unrestricted Bash(*) grant from 7 skills; none of the six
non-financial ones contained a single shell command. finance-expert
documents code that charges cards and reads bank accounts, so it now
grants no shell at all.
- Remove credential literals: Stripe keys, two JWT signing keys, an
Express session secret, a Redis password and WiFi credentials, all
inlined in examples. They load from the environment now.
- finance-expert: idempotency keys were documented but absent, so a
retry double-charged; webhook signature failures were not caught, so a
forged event raised uncaught instead of being rejected;
int(amount * 100) truncated fractions of a cent. All fixed, plus a
money-movement guardrails section.
- trading-expert: place_order routed without any pre-trade risk check
although a RiskManager sat unused in the next section. Risk validation
now runs before routing and raises rather than returning a boolean a
caller can ignore; live routing is opt-in.
- Correct an Ansible Vault example that showed plaintext under an
"encrypted" label.
Also fixes 8 broken documentation links and a prematurely closed code
fence in skill-creator-expert that leaked template content into prose.
Per the repository file-organization policy, four stale progress reports
(SKILLS_MANIFEST, COMPLETE_SKILLS_LIBRARY, COMPLETE_LIBRARY_MANIFEST,
PHASE_3_DATA_ANALYTICS) move out of stdlib/ into the gitignored
.roadmap/status/stdlib/; they claimed 31 of 100 skills complete. They
appear here as deletions because .roadmap/ is not tracked.
Reviewed-by: Security Analyst, Language Designer, DevX Engineer,
Documentation Specialist
* fix(skills): resolve standard library skills from their real layout
No stdlib skill was resolvable. SkillResolver looked for
`<stdlibDir>/<name>.md` with stdlibDir defaulting to `stdlib/skills`, a
directory that does not exist, and the path ignored the category level
the library actually uses. The two LSP providers had the same wrong
directory and scanned only one level deep, so neither completion nor
go-to-definition could see a skill either.
- skill-discovery.ts: enumerate skill entry points across the shapes in
use - a flat `<name>.md`, `<name>/SKILL.md`, and
`<category>/<name>/SKILL.md` - while skipping references/, scripts/
and assets/, which hold supporting material rather than entry points.
- skill-resolver.ts: point stdlibDir at `stdlib`, and look the name up
as a directory under any category as well as the two legacy shapes, so
existing custom stdlib directories keep working. The name is used as a
single path segment and rejected if it contains a separator or
traversal, so a reference cannot escape the stdlib root.
- Rewire both LSP providers onto the shared discovery helper.
Tests: 13 new cases covering the layouts, ordering, the references/
exclusion, path-traversal rejection, and an integration test that
resolves real shipped skills by bare name.
Reviewed-by: Compiler Engineer, Runtime Architect, Security Analyst
* feat(stdlib): add 17 skills covering the library's largest gaps
Selection was driven by cross-referencing coverage against observed usage
rather than by intuition: Stack Overflow and GitHub Octoverse data for
which technologies matter, and install rankings on public agent-skill
registries for the shape of skills people actually use.
That comparison found a mismatch of form, not only of coverage. The
most-installed skills in the ecosystem are procedures - tdd, refactoring,
frontend design, browser automation - while all 174 existing skills were
domain knowledge shaped as <domain>-expert. The new workflows/ category
closes that gap and introduces the <activity>-workflow convention.
New category workflows/ (4)
- tdd-workflow, refactoring-workflow, debugging-workflow,
code-review-workflow. code-review-workflow complements rather than
replaces code-review-expert: procedure versus judgement. Merge them if
the split proves confusing in use.
Applied AI (3) - the largest coverage gap
- llm-engineering-expert, rag-expert, agent-engineering-expert.
The library referenced LLMs in tags but covered none of it: pgvector
appeared zero times across 174 skills, LangChain once, MCP twice
despite the repository shipping an MCP integration guide.
Capabilities (2)
- document-processing-expert (PDF, DOCX, XLSX, PPTX in one skill),
browser-automation-expert (a client against third-party sites,
distinct from playwright-expert which tests your own application).
Data (3)
- mysql-expert, the second most used database and previously absent
while rarer stores had skills; analytical-databases-expert;
stream-processing-expert.
Security (3)
- secrets-management-expert, supply-chain-security-expert (OWASP A03
2025), identity-access-expert (OWASP A01).
Interface and meta (2)
- accessibility-expert: design/ held only design-expert, which despite
its name covers software architecture, so WCAG had no home.
- skill-router: find and compose skills across 191, with a
disambiguation table for overlapping pairs.
Grouping by decision context rather than by technology keeps the growth
to 17 skills for roughly 50 topics. Five vector stores live inside
rag-expert; four document formats inside document-processing-expert.
Per-tool depth sits in references/, which the progressive-disclosure work
in 3.0.0 made cheap.
Four further gaps are better served by extending existing skills -
PyTorch and TensorFlow in ml-expert, OpenTelemetry in monitoring-expert,
Pulumi and Crossplane in terraform-expert - and are not in this change.
Library 3.0.0 -> 3.1.0, additive only. Adds the workflows label to the
inventory generator; catalogue, inventory, structure and CHANGELOG
regenerated.
Reviewed-by: Product Strategist, Security Analyst, DevX Engineer,
Documentation Specialist
* fix(test): create test directories with mkdtempSync
CodeQL flagged js/insecure-temporary-file (CWE-377) on both suites.
`join(tmpdir(), <predictable name>)` followed by mkdirSync creates a
world-readable directory at a guessable path, so another local user can
pre-create it or plant a symlink between the name being computed and the
directory being created.
mkdtempSync creates the directory atomically with a random suffix and
0700 permissions, which closes both the disclosure and the race.
One occurrence is new in this branch (skill-discovery); the other
pre-dates it in skill-resolver and is fixed in the same pass rather than
left as a known finding in a file this branch already touches.
502 lines
16 KiB
Python
502 lines
16 KiB
Python
#!/usr/bin/env python3
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"""
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PCL Standard Library - Skill Catalog Generator
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Generates a searchable catalog of all skills in JSON and YAML formats
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for easy discovery and integration.
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Security: This script uses safe YAML loading and validates all file paths.
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"""
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import json
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import re
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import sys
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from collections import defaultdict
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from datetime import datetime
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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import yaml
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class SkillCatalogGenerator:
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"""Generate skill catalog from stdlib directory"""
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# Maximum file size to prevent DoS (10MB)
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MAX_FILE_SIZE = 10 * 1024 * 1024
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# Maximum description length. The catalog is the discovery surface, so it
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# carries the full description including its activation trigger; the
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# Agent Skills v1.0 ceiling is 1024 characters.
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MAX_DESCRIPTION_LENGTH = 1024
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def __init__(self, stdlib_path: str) -> None:
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"""
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Initialize the skill catalog generator.
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Args:
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stdlib_path: Path to the stdlib directory
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Raises:
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ValueError: If stdlib_path is not a valid directory
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"""
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self.stdlib_path = Path(stdlib_path).resolve()
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if not self.stdlib_path.is_dir():
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raise ValueError(f"Invalid stdlib path: {stdlib_path}")
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self.skills: List[Dict[str, Any]] = []
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self.categories: Dict[str, List[Dict[str, Any]]] = defaultdict(list)
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def find_skill_files(self) -> List[Path]:
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"""
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Find all skill entry points.
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A skill is a directory holding a SKILL.md, one level under its
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category: stdlib/<category>/<skill-name>/SKILL.md. Files under
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references/ are supporting material, never entry points.
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Returns:
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List of unique Path objects for skill files
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Raises:
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PermissionError: If directory cannot be accessed
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"""
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skill_files: List[Path] = []
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try:
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skill_files.extend(self.stdlib_path.glob("*/*/SKILL.md"))
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except PermissionError as e:
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print(f"Error: Permission denied accessing {self.stdlib_path}: {e}", file=sys.stderr)
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raise
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# Remove duplicates and ensure files are within stdlib_path
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unique_files = set(skill_files)
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validated_files = [
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f for f in unique_files
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if self._is_safe_path(f)
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]
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return sorted(validated_files)
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def _is_safe_path(self, file_path: Path) -> bool:
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"""
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Validate that file path is within stdlib directory (prevent path traversal).
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Args:
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file_path: Path to validate
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Returns:
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True if path is safe, False otherwise
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"""
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try:
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resolved_path = file_path.resolve()
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return resolved_path.is_relative_to(self.stdlib_path)
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except (ValueError, OSError):
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return False
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def parse_yaml_frontmatter(self, content: str) -> Dict[str, Any]:
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"""
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Extract YAML frontmatter from skill file using safe loading.
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Args:
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content: File content
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Returns:
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Dictionary of frontmatter data, empty dict if not found or invalid
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Security: Uses yaml.safe_load to prevent code execution
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"""
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# Match YAML frontmatter between --- markers
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match = re.match(r'^---\s*\n(.*?)\n---\s*\n', content, re.DOTALL)
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if not match:
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return {}
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try:
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# Use safe_load to prevent arbitrary code execution
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frontmatter = yaml.safe_load(match.group(1))
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return frontmatter if isinstance(frontmatter, dict) else {}
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except yaml.YAMLError as e:
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print(f"Warning: YAML parsing error: {e}", file=sys.stderr)
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return {}
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def extract_skill_info(self, file_path: Path) -> Optional[Dict[str, Any]]:
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"""
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Extract skill information from a skill file.
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Args:
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file_path: Path to skill file
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Returns:
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Dictionary with skill information, None if extraction fails
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Security: Validates file size and uses safe file reading
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"""
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try:
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# Check file size to prevent DoS
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file_size = file_path.stat().st_size
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if file_size > self.MAX_FILE_SIZE:
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print(f"Warning: Skipping large file {file_path} ({file_size} bytes)", file=sys.stderr)
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return None
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# Read file with explicit encoding
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with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
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content = f.read()
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# Parse frontmatter
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frontmatter = self.parse_yaml_frontmatter(content)
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# Determine skill name and category
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relative_path = file_path.relative_to(self.stdlib_path)
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if file_path.name == "SKILL.md":
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skill_name = file_path.parent.name
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category = file_path.parent.parent.name
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else:
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skill_name = file_path.stem # filename without extension
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category = file_path.parent.name
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# Extract description from frontmatter or content (sanitized)
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description = self._sanitize_string(
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frontmatter.get('description', '')
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)
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if not description:
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# Try to find description in first paragraph
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description = self._extract_description(content)
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# Progressive disclosure: the bulk of a skill lives in references/,
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# so size and example counts cover the whole skill, not SKILL.md alone.
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references = sorted(file_path.parent.glob('references/*.md'))
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whole = content
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total_size = file_size
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for ref in references:
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try:
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whole += '\n' + ref.read_text(encoding='utf-8', errors='ignore')
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total_size += ref.stat().st_size
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except (OSError, IOError):
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continue
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# Count lines of code examples
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code_blocks = re.findall(r'```[\s\S]*?```', whole)
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total_code_lines = sum(len(block.split('\n')) for block in code_blocks)
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# Sanitize and validate frontmatter fields
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return {
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'name': self._sanitize_string(frontmatter.get('name', skill_name)),
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'version': self._sanitize_string(str(frontmatter.get('version', '1.0.0'))),
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'category': self._sanitize_string(frontmatter.get('category', category)),
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'description': description[:self.MAX_DESCRIPTION_LENGTH],
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'tags': self._sanitize_list(frontmatter.get('tags', [])),
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'allowed_tools': self._sanitize_list(frontmatter.get('allowed-tools', [])),
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'path': str(relative_path).replace('\\', '/'), # Normalize path separators
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'references': [
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f'references/{ref.name}' for ref in references
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],
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'file_size': total_size,
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'total_lines': len(whole.split('\n')),
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'code_examples': len(code_blocks),
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'code_lines': total_code_lines
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}
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except (OSError, IOError) as e:
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print(f"Error reading {file_path}: {e}", file=sys.stderr)
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return None
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except Exception as e: # pylint: disable=broad-except
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print(f"Unexpected error processing {file_path}: {e}", file=sys.stderr)
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return None
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def _sanitize_string(self, value: Any) -> str:
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"""
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Sanitize string value for safe output.
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Args:
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value: Value to sanitize
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Returns:
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Sanitized string
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"""
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if not isinstance(value, str):
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value = str(value)
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# Remove control characters except newlines and tabs
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return ''.join(char for char in value if ord(char) >= 32 or char in '\n\t')
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def _sanitize_list(self, value: Any) -> List[str]:
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"""
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Sanitize list value for safe output.
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Args:
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value: Value to sanitize
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Returns:
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Sanitized list of strings
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"""
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if not isinstance(value, list):
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return []
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return [self._sanitize_string(item) for item in value if item]
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def _extract_description(self, content: str) -> str:
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"""
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Extract description from content.
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Args:
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content: File content
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Returns:
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First non-empty, non-heading line
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"""
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lines = content.split('\n')
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for line in lines:
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stripped = line.strip()
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if stripped and not stripped.startswith('#') and not stripped.startswith('---'):
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return self._sanitize_string(stripped)
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return ''
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def generate_catalog(self) -> Dict[str, Any]:
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"""
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Generate complete skill catalog.
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Returns:
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Dictionary containing complete catalog data
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"""
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print("Finding skill files...")
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skill_files = self.find_skill_files()
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print(f" Found {len(skill_files)} skill files")
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print("\nParsing skills...")
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for file_path in skill_files:
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skill_info = self.extract_skill_info(file_path)
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if skill_info:
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self.skills.append(skill_info)
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self.categories[skill_info['category']].append(skill_info)
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print(f" + {skill_info['name']}")
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# Sort skills by name
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self.skills.sort(key=lambda x: x['name'])
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# Generate statistics
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total_skills = len(self.skills)
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stats = {
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'total_skills': total_skills,
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'total_categories': len(self.categories),
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'total_code_lines': sum(s['code_lines'] for s in self.skills),
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'total_file_size': sum(s['file_size'] for s in self.skills),
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'avg_lines_per_skill': (
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sum(s['total_lines'] for s in self.skills) // total_skills
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if total_skills > 0 else 0
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),
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'categories': {cat: len(skills) for cat, skills in self.categories.items()}
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}
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# Get all unique tags
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all_tags: set = set()
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for skill in self.skills:
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all_tags.update(skill.get('tags', []))
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catalog = {
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'version': '2.0.0',
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'generated': datetime.now().strftime('%Y-%m-%d'),
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'statistics': stats,
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'tags': sorted(list(all_tags)),
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'categories': dict(self.categories),
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'skills': self.skills
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}
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return catalog
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def save_catalog(self, catalog: Dict[str, Any], output_dir: Path) -> None:
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"""
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Save catalog in JSON and YAML formats.
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Args:
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catalog: Catalog data to save
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output_dir: Output directory path
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Raises:
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OSError: If file writing fails
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"""
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# Create output directory with safe permissions
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output_dir.mkdir(parents=True, exist_ok=True, mode=0o755)
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# Save as JSON with safe encoding
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json_path = output_dir / 'skill-catalog.json'
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with open(json_path, 'w', encoding='utf-8') as f:
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json.dump(catalog, f, indent=2, ensure_ascii=False, sort_keys=True)
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print(f"\nJSON catalog saved to: {json_path}")
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# Save as YAML
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yaml_path = output_dir / 'skill-catalog.yaml'
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with open(yaml_path, 'w', encoding='utf-8') as f:
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yaml.dump(catalog, f, default_flow_style=False, sort_keys=False, allow_unicode=True)
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print(f"YAML catalog saved to: {yaml_path}")
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# Save simplified index (just names and categories)
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index = {
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'version': catalog['version'],
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'total_skills': catalog['statistics']['total_skills'],
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'skills': [
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{
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'name': s['name'],
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'category': s['category'],
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'path': s['path'],
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'tags': s.get('tags', [])
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}
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for s in catalog['skills']
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]
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}
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index_path = output_dir / 'skill-index.json'
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with open(index_path, 'w', encoding='utf-8') as f:
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json.dump(index, f, indent=2, ensure_ascii=False, sort_keys=True)
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print(f"Index saved to: {index_path}")
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# Generate README with statistics
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self.generate_catalog_readme(catalog, output_dir)
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def generate_catalog_readme(self, catalog: Dict[str, Any], output_dir: Path) -> None:
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"""
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Generate README for catalog directory.
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Args:
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catalog: Catalog data
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output_dir: Output directory path
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"""
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stats = catalog['statistics']
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readme_content = f"""# PCL Standard Library - Skill Catalog
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Auto-generated catalog of all {stats['total_skills']} skills in the PCL Standard Library.
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## 📊 Statistics
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- **Total Skills**: {stats['total_skills']}
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- **Categories**: {stats['total_categories']}
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- **Total Code Lines**: {stats['total_code_lines']:,}
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- **Total File Size**: {stats['total_file_size'] // 1024:,} KB
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- **Average Lines/Skill**: {stats['avg_lines_per_skill']}
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## 📁 Skills by Category
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"""
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for category, count in sorted(stats['categories'].items(), key=lambda x: -x[1]):
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readme_content += f"- **{category}**: {count} skills\n"
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readme_content += f"""
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## 🏷️ Available Tags
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{', '.join(f'`{tag}`' for tag in sorted(catalog['tags']))}
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## 📄 Catalog Files
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- **skill-catalog.json** - Complete catalog with all metadata (JSON)
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- **skill-catalog.yaml** - Complete catalog with all metadata (YAML)
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- **skill-index.json** - Lightweight index (names, categories, paths only)
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## 🔍 Using the Catalog
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### Load catalog in Python
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```python
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import json
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with open('skill-catalog.json', encoding='utf-8') as f:
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catalog = json.load(f)
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# Find all Python skills
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python_skills = [
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skill for skill in catalog['skills']
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if 'python' in skill['name'].lower() or 'python' in skill.get('tags', [])
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]
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|
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# Find skills by category
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devops_skills = catalog['categories']['devops']
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|
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# Search by tag
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web_skills = [
|
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skill for skill in catalog['skills']
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if 'web' in skill.get('tags', [])
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]
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```
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|
|
### Load catalog in JavaScript
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|
|
|
```javascript
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const catalog = require('./skill-catalog.json');
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|
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// Find all frontend skills
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const frontendSkills = catalog.skills.filter(skill =>
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skill.tags.includes('frontend') || skill.tags.includes('web')
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);
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|
|
// Get category statistics
|
|
console.log(catalog.statistics.categories);
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|
```
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## 🔗 Related Documentation
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|
|
- [Standard Library README](../README.md)
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|
- [Skills Inventory](../SKILLS_INVENTORY.md)
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|
- [Directory Structure](../DIRECTORY_STRUCTURE.md)
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|
|
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---
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|
|
**Generated**: {catalog['generated']}
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|
**Version**: {catalog['version']}
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|
"""
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|
|
|
readme_path = output_dir / 'README.md'
|
|
with open(readme_path, 'w', encoding='utf-8') as f:
|
|
f.write(readme_content)
|
|
print(f"Catalog README saved to: {readme_path}")
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|
|
def main() -> int:
|
|
"""
|
|
Main entry point.
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|
|
Returns:
|
|
Exit code (0 for success, 1 for error)
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|
"""
|
|
try:
|
|
# Determine stdlib path
|
|
script_dir = Path(__file__).parent.resolve()
|
|
stdlib_path = script_dir.parent / 'stdlib'
|
|
output_dir = stdlib_path / 'catalog'
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|
|
|
print("=" * 60)
|
|
print("PCL Standard Library - Skill Catalog Generator")
|
|
print("=" * 60)
|
|
print(f"\nStdlib path: {stdlib_path}")
|
|
print(f"Output path: {output_dir}\n")
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|
|
|
# Validate stdlib path exists
|
|
if not stdlib_path.is_dir():
|
|
print(f"Error: Stdlib directory not found: {stdlib_path}", file=sys.stderr)
|
|
return 1
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|
|
|
# Generate catalog
|
|
generator = SkillCatalogGenerator(str(stdlib_path))
|
|
catalog = generator.generate_catalog()
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|
|
|
# Save catalog
|
|
generator.save_catalog(catalog, output_dir)
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|
|
|
print("\n" + "=" * 60)
|
|
print("Catalog generation complete!")
|
|
print("=" * 60)
|
|
print(f"\nGenerated catalog with {catalog['statistics']['total_skills']} skills")
|
|
print(f"Files saved to: {output_dir}")
|
|
|
|
return 0
|
|
|
|
except KeyboardInterrupt:
|
|
print("\n\nOperation cancelled by user", file=sys.stderr)
|
|
return 130
|
|
except Exception as e: # pylint: disable=broad-except
|
|
print(f"\nError: {e}", file=sys.stderr)
|
|
return 1
|
|
|
|
|
|
if __name__ == '__main__':
|
|
sys.exit(main())
|