* 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withdrawn.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.
10 KiB
name, version, description, category, tags, allowed-tools, metadata
| name | version | description | category | tags | allowed-tools | metadata | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| skill-router | 1.0.0 | Find the right skill in the PCL standard library and compose several when a task spans domains. Use when the user asks which skill applies, cannot find a capability, wants to know what the library covers, is starting a task that spans several domains, or when the task involves choosing between overlapping skills, discovering skills by keyword, or deciding whether a new skill is needed. | tools |
|
|
|
Skill Router
The library holds 191 skills across 15 categories. This skill answers which ones apply to a task, and how to combine them.
Core Concepts
Route on the Task, Not the Technology
"Fix this slow query" is not a PostgreSQL question until you know the query is in PostgreSQL. Start from what the user is trying to do, then narrow by the technology actually in the repository.
Two Shapes of Skill
| Shape | Naming | Answers | Examples |
|---|---|---|---|
| Domain expertise | <domain>-expert |
"How does X work, and what is good practice?" | postgresql-expert, react-expert |
| Procedure | <activity>-workflow |
"What do I do, in what order?" | tdd-workflow, debugging-workflow |
A task usually needs one of each: the workflow drives the sequence, the expert supplies the judgement inside it.
Compose, Don't Concatenate
Loading five skills fills the context and dilutes attention. Load the workflow plus the one or two experts whose material the task actually touches, and consult a third only if the work reaches it.
Finding a Skill
The catalogue is machine-readable and is the fastest route:
# By keyword across names, descriptions and tags
jq -r '.skills[] | select(
(.name + " " + .description + " " + (.tags | join(" ")))
| ascii_downcase | contains("kafka")
) | "\(.category)/\(.name)"' stdlib/catalog/skill-catalog.json
# Everything in a category
jq -r '.skills[] | select(.category == "security") | .name' stdlib/catalog/skill-index.json
# What a skill covers, before loading it
jq -r '.skills[] | select(.name == "rag-expert") | .description' stdlib/catalog/skill-catalog.json
Or by filesystem, which is often quicker for a name you half-remember:
find stdlib -maxdepth 2 -type d -name '*postgres*'
grep -rl "watermark" stdlib --include=SKILL.md
Every description contains an explicit Use when … clause naming the keywords
and tasks that should select it. Read that clause rather than guessing from the
name.
The Category Map
| Category | Holds | Reach for it when |
|---|---|---|
workflows/ |
Procedures: TDD, refactoring, debugging, code review | The question is "how do I proceed?" |
languages/ |
23 programming languages | Idiom, tooling, or language-specific behaviour |
frameworks/ |
15 web, mobile and desktop frameworks | Framework conventions and lifecycle |
api/ |
REST, GraphQL, gRPC, OpenAPI, microservices | Designing or consuming an interface |
data/ |
Databases, warehouses, pipelines, BI | Storage, queries, analytics, streaming |
devops/ |
Containers, orchestration, IaC, CI/CD, observability | Build, deploy, run |
cloud/ |
AWS, Azure, GCP, Cloudflare | Provider-specific services |
ai/ |
ML, LLM engineering, RAG, agents | Anything model-based |
security/ |
AppSec, identity, secrets, supply chain, compliance | A security question, at any stage |
qa/ |
Test frameworks, load, chaos | Writing or running tests |
tools/ |
Git, documents, browsers, chat platforms, this skill | Working with a tool rather than a domain |
domains/ |
Industry verticals and enterprise platforms | Domain rules: healthcare, finance, SAP |
professional/ |
Accounting, legal, banking, FinOps, standards | Non-engineering expertise |
scientific/ |
Research, quantum, biology | Scientific computing |
design/ |
Architecture patterns, accessibility | Structure or interface quality |
Note that design/design-expert covers software architecture, not visual
design — a legacy naming artefact. accessibility-expert is the interface skill.
Choosing Between Overlapping Skills
Several pairs look similar. The distinctions that matter:
| If the task is… | Use | Not |
|---|---|---|
| Driving a browser to test your own app | playwright-expert |
browser-automation-expert |
| Driving a browser to get data from a site | browser-automation-expert |
playwright-expert |
| The process of reviewing a change | code-review-workflow |
code-review-expert |
| What good code looks like per dimension | code-review-expert |
code-review-workflow |
| A security breach investigation | incident-response-expert |
debugging-workflow |
| A production defect, no attacker | debugging-workflow |
incident-response-expert |
| Transactional workload, rows | postgresql-expert, mysql-expert |
analytical-databases-expert |
| Aggregates over huge tables | analytical-databases-expert |
postgresql-expert |
| Moving events continuously | stream-processing-expert |
airflow-expert |
| Scheduled batch orchestration | airflow-expert |
stream-processing-expert |
| Prompt design and model output | llm-engineering-expert |
agent-engineering-expert |
| A model that calls tools | agent-engineering-expert |
llm-engineering-expert |
| Answering over your documents | rag-expert |
elasticsearch-expert |
Composition Patterns
Common tasks and the skills that serve them:
"Add a feature to our API, test-first"
tdd-workflow (the loop) → api-design-expert (contract) → the language skill →
code-review-workflow (before merge)
"Our checkout is slow"
debugging-workflow (method) → performance-expert (measurement) → the database
or framework skill, once measurement says which
"Build an assistant over our documentation"
rag-expert (retrieval) → llm-engineering-expert (generation and evaluation) →
agent-engineering-expert (only if it calls tools) → identity-access-expert
(who may see which documents)
"Harden our release pipeline"
supply-chain-security-expert (provenance, SBOM) → cicd-expert (pipeline) →
secrets-management-expert (credentials)
"Make the dashboard accessible"
accessibility-expert (conformance) → the framework skill (implementation) →
qa-expert (regression coverage)
"Migrate a large table with no downtime"
refactoring-workflow (parallel change) → the database skill (mechanics) →
sre-expert (rollout and rollback)
When No Skill Fits
Before concluding a skill is missing:
- Search the catalogue by tag, not by the name you expected.
- Check
references/— the topic may be a section inside a broader skill.railslives inruby-expert,sparkindatabricks-expertandanalytical-databases-expert. - Check whether a broader skill covers it.
vector-databasesis insiderag-expertby design, because the choice only matters in that context.
If it is genuinely absent, the test for adding one is whether it is a distinct decision context rather than a distinct technology. Five vector stores share one mental model and belong in one skill with per-store references; MySQL and PostgreSQL differ enough in design consequences to warrant separate skills.
Use skill-creator-expert to author it, and scripts/validate-skills.py to
check conformance.
Best Practices
- Read the
Use whenclause before loading a skill; it is written to be the routing signal. - Start with the workflow when the question is procedural — it will name the expert skills it needs.
- Load two or three skills, not six. Add a fourth when the work reaches it.
- Prefer the specific skill.
mysql-expertoversql-expertwhen the database is MySQL. - Consult
security/early, not as a final review — the cheapest security fixes are design decisions. - Follow the reference links rather than loading a second skill for a detail;
references/is where the depth lives.
Anti-Patterns
- Routing on a keyword in isolation. "Java" in "JavaScript" is not
java-expert. - Loading every plausibly related skill — dilutes attention and fills the context budget.
- Picking the general skill when a specific one exists.
- Skipping the workflow skill and improvising the procedure.
- Assuming a topic is missing because the skill is not named after it.
Resources
stdlib/catalog/skill-index.json— name, category, path, tagsstdlib/catalog/skill-catalog.json— full descriptions, sizes, reference listsstdlib/SKILLS_INVENTORY.md— human-readable listing by categorystdlib/CHANGELOG.md— versioning and migration notesskill-creator-expert— authoring a new skill