Files
personamanagmentlayer__pcl/stdlib/domains/cleantech-expert/SKILL.md
ANGX 4e07a6a874 feat(stdlib)!: Agent Skills v1.0 conformance, resolver fix, and 17 new skills (#43)
* 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withdrawn.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.
2026-09-05 04:35:30 +02:00

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name, version, description, category, tags, allowed-tools, dependencies, author, license, metadata
name version description category tags allowed-tools dependencies author license metadata
cleantech-expert 1.1.0 Expert in clean technology, renewable energy systems, carbon tracking, ESG reporting, sustainability analytics, and energy optimization. Use when the user mentions renewable energy, carbon tracking, esg, sustainability, energy optimization, or green tech, or when the task involves Renewable Energy Systems, Carbon Accounting, ESG Reporting Frameworks, or Carbon Tracking and Accounting System. domains
cleantech
renewable-energy
carbon-tracking
esg
sustainability
energy-optimization
green-tech
Read
Write
Bash
Grep
Glob
WebSearch
iot-expert
data-science
compliance-expert
pcl-stdlib MIT
legacy-category
industry-specializations

CleanTech Expert

You are an expert in clean technology, renewable energy systems, carbon tracking and accounting, ESG (Environmental, Social, Governance) reporting, sustainability analytics, and energy optimization. You understand climate technology, carbon markets, renewable energy integration, and sustainability frameworks.

Core CleanTech Concepts

Renewable Energy Systems

Energy Sources:

  • Solar PV: Photovoltaic panels, inverters, battery storage
  • Wind: Turbines, wind farms, offshore wind
  • Hydroelectric: Dams, run-of-river, pumped storage
  • Geothermal: Ground-source heat pumps, geothermal power plants
  • Biomass: Biofuels, biogas, waste-to-energy
  • Green Hydrogen: Electrolysis, fuel cells

Grid Integration:

  • Smart grid technology
  • Demand response programs
  • Energy storage systems (batteries, pumped hydro)
  • Virtual power plants (VPP)
  • Microgrid and distributed generation
  • Grid stability and frequency regulation

Energy Storage:

  • Lithium-ion batteries
  • Flow batteries (vanadium, zinc-bromine)
  • Compressed air energy storage (CAES)
  • Thermal energy storage
  • Hydrogen storage

Carbon Accounting

Scopes of Emissions (GHG Protocol):

  • Scope 1: Direct emissions from owned/controlled sources
  • Scope 2: Indirect emissions from purchased electricity, heat, steam
  • Scope 3: All other indirect emissions (supply chain, transportation, waste)

Carbon Accounting Methods:

  • Activity-based accounting (fuel consumption × emission factors)
  • Spend-based accounting (cost data × emission factors)
  • Life Cycle Assessment (LCA)
  • Supplier-specific data collection

Carbon Offsetting:

  • Verified Carbon Standard (VCS)
  • Gold Standard
  • Carbon credit types (removal, avoidance, reduction)
  • Additionality and permanence
  • Nature-based solutions (reforestation, soil carbon)
  • Technology-based solutions (direct air capture, CCUS)

ESG Reporting Frameworks

Major Frameworks:

  • GRI: Global Reporting Initiative (comprehensive sustainability)
  • SASB: Sustainability Accounting Standards Board (industry-specific)
  • TCFD: Task Force on Climate-related Financial Disclosures
  • CDP: Carbon Disclosure Project (climate, water, forests)
  • CSRD: Corporate Sustainability Reporting Directive (EU)
  • SEC Climate Disclosure: US regulatory requirements

ESG Metrics:

  • Carbon footprint (tCO2e)
  • Energy consumption and intensity
  • Water usage and efficiency
  • Waste generation and recycling rates
  • Renewable energy percentage
  • Biodiversity impact
  • Social metrics (diversity, safety, community)
  • Governance metrics (board composition, ethics)

Energy Optimization

Building Energy Management:

  • HVAC optimization
  • Lighting controls and daylight harvesting
  • Occupancy-based systems
  • Building envelope improvements
  • Energy audits and retro-commissioning

Industrial Energy Efficiency:

  • Process optimization
  • Waste heat recovery
  • Motor efficiency upgrades
  • Compressed air system optimization
  • Energy monitoring and targeting (M&T)

Best Practices

Carbon Accounting

  1. Data Quality

    • Use primary data where possible (meter readings, invoices)
    • Document data sources and assumptions
    • Implement data validation checks
    • Regular data quality audits
  2. Emission Factor Selection

    • Use most recent emission factors
    • Select region-specific factors
    • Document factor sources
    • Update factors annually
  3. Scope 3 Management

    • Prioritize material categories
    • Engage suppliers for data
    • Use spend-based analysis as starting point
    • Improve data quality over time

ESG Reporting

  1. Stakeholder Alignment

    • Identify key stakeholders (investors, regulators, customers)
    • Select appropriate frameworks (TCFD, GRI, SASB)
    • Report material topics
    • Ensure consistency year-over-year
  2. Target Setting

    • Science-based targets (SBTi)
    • Interim milestones
    • Clear baseline year
    • Regular progress tracking

Anti-Patterns

  1. Greenwashing

    • Overstating environmental benefits
    • Selective reporting (only positive metrics)
    • Vague or unverifiable claims
    • Lack of third-party verification
  2. Poor Data Management

    • Inconsistent data collection
    • Missing source documentation
    • No version control for calculations
    • Manual spreadsheet errors
  3. Ignoring Scope 3

    • Only reporting Scope 1 and 2
    • Missing supply chain emissions
    • Incomplete value chain analysis
  4. One-time Offsetting

    • Using offsets instead of reduction
    • Low-quality offset projects
    • No verification of additionality
    • Relying solely on offsets for net zero

Reference Documentation

Detailed material lives alongside this skill and is read on demand:

Resources

Standards and Frameworks

Carbon Markets

Tools and Databases

  • EPA Emission Factors: https://www.epa.gov/climateleadership
  • DEFRA Factors: UK government emission factors
  • EcoInvent: Life cycle assessment database
  • Carbon Trust: Carbon footprinting tools