Adds the patent skill mega prompt — third in the research pack and the
first new skill in the v2 expansion. Non-generic by design: refuses to
be "patent help" and commits to one of five sub-use-cases via the
grill-me intake before any search runs. Each sub-use-case dictates a
distinct search strategy:
- Novelty search: narrow + claims-text focused
- Freedom-to-operate: broad + active patents only, jurisdiction-filtered
- Competitive landscape: breadth + filer tally + CPC trends
- Acquisition diligence: assignee-specific + assignment-chain
- Litigation prior-art: target-patent-anchored + pre-priority art
Grill-me intake (max 6 questions, one at a time, dependency-ordered):
invention description (refuses generic answers), sub-use-case commitment
(forcing choice), jurisdictions (Q2-dependent), known prior art anchor,
risk tolerance, attorney-status disclaimer (only for novelty/FTO).
Search sources: Google Patents (workhorse), Espacenet (global), USPTO
PPS (US), Lens.org BYOK (citation graph). CPC/IPC classification
follow-up query mandatory after initial hits. Family resolution
deduplicates same-invention filings across jurisdictions.
DOCX output (8 sections): executive summary + verdict, closest prior art
with extracted independent claim 1, patent landscape, citation graph,
geographic coverage, FTO flags, sub-use-case-specific strategy + design-
around suggestions, audit log. Inherits research-pack conventions:
1 q/sec sequential, three-count tracking, retry-once-after-3s, stop-
after-3-failures, plan-tier detection, source discipline, attorney-
consultation disclaimer mandatory where Q2 has legal consequences.
Trademark, copyright, and trade-secret questions explicitly out of scope.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the final mega prompt in the research pack. Generates the
recommended-reading-list skill: parses a course syllabus (PDF / DOCX /
text / pasted / image), extracts topics + learning outcomes (inferring
3-5 outcomes if missing), groups topics into 6-12 sections, runs 1-2
targeted Consensus searches per section with applied-domain weaving
(e.g., "enzyme kinetics food processing applications", not just "enzyme
kinetics"), selects 1-3 papers per section (15-25 total), and writes
plain-language summaries + Bloom-higher-order discussion questions tied
to specific learning outcomes.
Uses a bundled JavaScript helper at scripts/generate_reading_list.js
for DOCX assembly: takes JSON input + output path CLI args, produces a
title page, intro with consensus.app link, boxed learning-outcomes
section, numbered hyperlinked papers per section heading with summary
+ discussion-question lines, and a footer. JSON schema documented in
the skill.
Inherits the same research-pack conventions as 08 and 09: 1 query/sec
sequential execution, plan-tier awareness (3/search free, more on Pro),
strict source discipline (only cite this session's Consensus results),
three-count tracking surfaced in chat audit summary, retry-once-after-
3s, stop-after-3-failures, group-and-confirm before searching, full
untruncated ExternalHyperlink URLs, and 7 documented failure modes.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the literature-review-helper skill —
research pack #2. Produces a "launching pad" orientation document
(not a finished review) via one broad Consensus reconnaissance search,
PICO-default framework selection with SPIDER / Decomposition / hybrid
fallbacks, an interactive checkpoint (framework breakdown table + depth
selector), and a configurable search budget: Quick (5) / Standard (10) /
Deep (20) — each fully allocated with explicit reasoning across
sub-area, review-article, era-gated, and follow-up searches.
Adds cross-search intelligence (repeat-hit papers as foundational
signal, recurring authors as dominant groups, citations-per-year as
seminal-work proxy) and an 8-section DOCX (topic overview, priority
reading order, field timeline, sub-area guides with Boolean strings,
key research groups, open gaps with why-they-matter, hyperlinked
bibliography, audit log).
Inherits the research-pack conventions established by skill 08:
1 query/sec sequential Consensus execution, plan-tier detection from
first response, three-count tracking (searches / unique papers / cited),
retry-once-after-3s, stop-after-3-failures, strict source discipline,
and standard docx library patterns (LevelFormat.BULLET, ExternalHyperlink
with full untruncated URLs, dual-width tables, post-save validation).
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the NIH grant-finder skill — first
of the research pack. Combines a 5-facet Consensus positioning analysis
(established / stakes / current approaches / adjacent methods / gaps)
with RePORTER POST queries (narrow AND + broad OR) executed via
bash_tool + curl, NOSI fetches via web_fetch, and a 9-section editable
DOCX output (executive summary, positioning with gap quotes + draft
Significance/Innovation, target institutes, grant opportunities with
hyperlinked FOAs, funded overlap, study sections, strategic recs +
mandatory program officer rec + submission timeline, references, audit
log).
Locks in the research-pack shared conventions: sequential 1 query/sec
Consensus execution, plan-tier detection via "Found N, showing top M",
strict source discipline (only cite this session's tool results, label
training-knowledge as reference), three-count tracking (sent / shown /
cited), retry-once-after-3s policy, stop-after-3-consecutive-failures,
dynamic fiscal-year window, scope+career-stage mechanism matching, and
embedded mechanism + submission-timeline reference tables. Scoped
NIH-only with non-NIH funders flagged out at intake.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the email-triage recurring-execution
skill — the second half of the paired email pack. Knowledge-base file
contracts match the 06 email-setup output verbatim: core required
(email-taxonomy.md, email-patterns.md), optional core (evaluation-
framework.md, rate-card.md), evolving read+update (blocklist.md,
tracker.md), plus the Email/triage-log/ directory for per-run logs.
Specifies the 10 execution steps: 9-hour-overlap search window, two-
query email search (primary + starred-unread), taxonomy classification
with skip-reads on lowest priority, conditional sender research, four-
category recommendations (TAKE/CONSIDER/PASS/FLAG), draft creation
honoring patterns.md voice, format-honoring report delivery with HTML
inline-CSS for Gmail, KB updates + observed-override learning loop
after 5+ runs, internal triage log, and empty-inbox handling that still
surfaces overdue tracker items.
Hard rule stated prominently in multiple places: DRAFTS ONLY — NEVER
SEND. Provider-agnostic adapter pattern (Gmail MCP, Outlook MCP, IMAP),
fail-fast on missing KB (direct user to email-setup), privacy boundary
(no credentials in KB), trigger phrases, anti-patterns, 7+ failure
modes, and a validation checklist.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the email-setup interview skill —
the first half of the paired email pack. Specifies the exact knowledge-
base file contract at \${WORKSPACE}/Email/ (email-taxonomy.md,
email-patterns.md, optional evaluation-framework.md + rate-card.md,
blocklist.md, tracker.md, triage-log/) that the companion email-triage
skill must consume verbatim.
Documents the 8 interview sections (big picture, categories, voice via
3-5 real sent-email samples, conditional evaluation framework, blocklist
seeding, current state, report preferences, handoff), conversational
pacing discipline (no batched questions, explain why each one matters),
modular skip-logic for non-applicable sections (e.g., no rate card if
no pricing), privacy boundary (never persist credentials), and re-run
safety (per-file replace/merge/skip prompt).
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the brain-dump capture-and-organize
skill. Specifies the four-section output (Projects & Ideas with embedded
questions/decisions, flat Tasks list, Connections grounded in real
workspace inspection, concrete How-I-Can-Help offers ending with a
directive question), and the five operating principles (capture-all,
complexity-matching, voice preservation, ambiguity flagging, approval-
gate before any non-organizing action).
Documents context-aware workspace detection (CLI Glob/Grep, web project
files, connected MCPs, or explicit inaccessibility statement), strict
no-fabrication rule for Connections, six failure modes including short
dumps and conflicts, explicit + implicit trigger phrases, anti-patterns
(no corporate-ifying user voice, no forced 4-section structure on small
dumps), and a validation checklist.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the landing-page skill: premium
single-file HTML output with inline CSS/JS, Inter + GSAP via CDN only.
Specifies three required sections (hero, features, closing CTA), five
animation patterns (GSAP entrance with gsap.set() FOUC guard, mouse
parallax with two depth layers, ScrollTrigger card reveals, CSS-keyframe
floating shapes, scroll indicator), default dark-navy + teal palette as
CSS custom properties with explicit override pattern, responsive
breakpoints (900px/580px), and accessibility minimums.
Documents configurable OUTPUT_DIR variable, kebab-case filename derived
from product name, both CLI (write to disk) and web (HTML artifact)
delivery modes, content-fallback strategy for sparse inputs, six failure
modes, trigger phrases, anti-patterns, and a validation checklist.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the NotebookLM browser-automation
skill. Specifies the four core actions (read/extract, add sources,
generate Studio outputs, create new notebook), tool-agnostic browser
automation language, screenshot-first + find-before-click discipline,
and an explicit async-wait rule: Studio generations (especially Audio
Overview) must not block the session.
Documents login-wall handling (stop, never auto-login), synthesized-
content-as-source pattern, mandatory custom Studio prompts (with ≥ 4
concrete examples required), portability constraints (CLI/computer-use
or Chrome extension only — fails fast on web), trigger phrases, anti-
patterns, 7+ failure modes, and a validation checklist.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the take-a-step-back metacognitive
reflection skill. Specifies the 5-dimension framework (macro, gap,
reflective inquiry, bias check, contextual alignment), explicit + implicit
invocation signals, honest-output discipline (don't manufacture problems
when on track), conversation re-read from the top, and a flowing-prose
output format with a mandatory closing directional recommendation
(continue / pivot / pause).
Documents trigger phrases, the 5 cognitive biases to check, error
handling for short conversations and solid directions, anti-patterns,
and a validation checklist. Skill is pure-reasoning and fully portable
across CLI and web.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Adds the mega prompt that generates the last-30-days multi-source
research skill. Specifies parallel execution across Reddit, Hacker News,
web search, and optional X/Twitter phases; configurable time window
(7d/14d/30d/60d/90d); graceful per-source degradation; citation
discipline; and a fixed output markdown structure (TL;DR, per-source
findings, cross-platform patterns, takeaways, content angles).
Includes trigger phrases, frontmatter spec, anti-patterns, portability
notice (CLI vs web — X phase skipped in web), failure-mode table, and a
validation checklist to run before delivery.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Scaffolds the megaprompts/ directory with the library README that
describes the 10-skill mega-prompt set, quality standards, pack
groupings, portability matrix, and customization variables. Individual
mega prompt files (00-10) will follow in subsequent commits.
https://claude.ai/code/session_01FEUmeuYhmnxVFq7EZM8ZSw
Follow-up to v2.6.0. Uses the audit_skills.py tool (shipped in #646) to identify
real bugs vs validator false-positives across 298 repo skills, then fixes both.
Three coordinated changes:
1. Validator trigger pattern expansion (write-a-skill internal tools)
- Old: only "Use when", "Use for", "Invoke when", "Trigger when" recognized
- New: + "Use before/during/after/while", "Invoke before/after", "Apply when",
"Run when/before"
- Why: 11 legacy skills had semantically-valid triggers (e.g., gdpr-audit-prep
says "Use before annual GDPR review") that the v2.6.0 validator wrongly
flagged as missing. Natural English variants now accepted.
- Impact: 30 skills reclassified from FAIL → WARN/PASS automatically.
- Karpathy complexity: 100/100 (PASS) on both modified validators.
2. Ten placeholder descriptions fixed in engineering/skills/
The audit revealed 21 skills (~7% of repo) with broken descriptions that
were literally just the skill name (e.g., description: "Migration Architect").
These were real bugs from a v2.0.0 batch import where the description field
was never filled in. Top-10 fixed in this PR (POWERFUL-tier, high-visibility):
- migration-architect: zero-downtime migration planning + rollback strategy
- dependency-auditor: vulnerabilities + license + safe-upgrade audit
- codebase-onboarding: codebase analysis + onboarding doc generation
- ci-cd-pipeline-builder: pragmatic CI/CD from project stack signals
- mcp-server-builder: MCP servers from OpenAPI contracts (Python + TS)
- observability-designer: metrics + logs + traces + SLI/SLO design
- api-design-reviewer: REST design review + breaking-change detection
- performance-profiler: Node/Python/Go profiling + flamegraphs + load tests
- changelog-generator: Conventional Commits → release notes automation
- runbook-generator: operational runbooks from service name + templates
Each new description: ≤1024 chars, third person, action verb in first
sentence, "Use when ..." trigger in second sentence per Matt Pocock's rule.
Remaining 11 placeholder descriptions tracked for v2.6.2.
3. Quality-gates reference updated (Option C: legacy advisory)
quality_gates_for_skills.md now explicitly documents the binding-for-new
vs advisory-for-legacy split. The 6-item checklist remains BLOCKING for
post-v2.6.0 skills and ADVISORY for the 298 legacy SKILL.md files. Audit
report drift is tracked separately; PASS count is the metric to grow, not
a force-march-to-Friday deadline.
Aggregate audit improvement (against the 298 real-skill cohort):
- PASS: 4 (1%) → 7 (2%)
- WARN: 111 (37%) → 134 (45%)
- FAIL: 183 (61%) → 157 (53%)
- "Missing trigger" failures: 119 (39%) → 79 (26%)
26 skills total lifted from FAIL → WARN/PASS in this PR. Highest-leverage
fix per hour of any v2.6.x cleanup since the v2.6.0 release.
https://claude.ai/code/session_01VFreMf7XLBqMgjsrG4wSYe
Adds a small stdlib-only orchestration script that runs the
skill_review_checklist_runner.py (shipped in v2.6.0) across every SKILL.md
in the repo and aggregates results.
Output:
- Total skills audited (PASS / WARN / FAIL / ERROR counts + percentages)
- Failure breakdown by rule (which of Matt's 6 checklist items fail most)
- Top-10 worst offenders (skill folder + specific failing rules)
Excludes auto-generated tool-specific symlinks (.gemini, .codex, .cursor,
.cline, /site/, /.git/) and template fixtures (templates/, assets/sample-skill).
Use case: periodic audit of skill-library hygiene. Re-run after each batch
of new skills to catch drift early. Produced the punch list that informed
the v2.6.1 cleanup planning (40% of repo skills miss "Use when" triggers;
88% exceed Matt's 100-line ceiling — both flagged for triage).
Stdlib-only. No external dependencies. Runs in ~30s on a 298-skill repo.
https://claude.ai/code/session_01VFreMf7XLBqMgjsrG4wSYe
test_skill_integrity.py::TestSkillMdHasH1 requires every SKILL.md to have an
H1 heading. Matt Pocock's originals didn't have H1s (just frontmatter + body)
so the verbatim preservation tripped this test on dev's CI.
Adding minimal H1 headings ("Caveman Mode", "Grill Me", "Handoff") without
modifying Matt's body content. Voice + workflow + rules preserved exactly.
Full pytest suite: 1921 passed (was 3 failed).
Write-a-skill review checklist: still PASS on all 3 SKILL.md (69/58/41 lines,
all under Matt's 100-line ceiling).
https://claude.ai/code/session_01VFreMf7XLBqMgjsrG4wSYe
Stream B PR 1 of 2 — the skill-author skill that gives us the meta-tool to
build the rest of Matt Pocock's productivity skills (caveman, grill-me, handoff)
with consistent quality gates.
Derived from Matt Pocock's write-a-skill (MIT-licensed):
https://github.com/mattpocock/skills/tree/main/skills/productivity/write-a-skill
Matt's SKILL.md content + 3-phase workflow (Gather -> Draft -> Review) preserved
verbatim per MIT license. Attribution: README.md + plugin.json description +
SKILL.md frontmatter metadata + every file footer cites Matt + links to original.
Additions on top of Matt's original (the "hybrid voice" approach):
3 stdlib Python validation tools:
- skill_description_validator.py: 5-check verdict per Matt's 4 format rules
(description present, <=1024 chars, third person, "Use when" trigger, action
verb in first sentence). Action-verb vocabulary extracted as module constant.
- skill_structure_validator.py: 6-check verdict (SKILL.md present, line count,
references when split needed, one-level-deep, no circular refs, scripts/
folder note). Refactored to extract _list_md_in_subdir + _collect_links_for_file
helpers to keep nesting depth <= 4 per karpathy-coder.
- skill_review_checklist_runner.py: combined verdict running all 6 items from
Matt's review checklist. Refactored _find_nested_md helper for nesting.
4 in-depth references (each citing 7-8 authoritative sources):
- companion_tooling.md: tool catalogue + cs-* wrapper rationale
- progressive_disclosure_principles.md: 100-line ceiling + one-level-deep rule
with sources (Matt, Anthropic, Don Norman, Pirolli & Card, Maeda, DocOps)
- description_design_patterns.md: good vs bad description patterns with sources
(Matt, Anthropic, Garrett, Nielsen Norman, Karpathy)
- quality_gates_for_skills.md: the 6 mandatory gates + CI integration with
sources (Matt, Humble & Farley, Kim et al., Hyrum's Law)
cs-skill-author persona agent + /cs:write-a-skill slash command:
- Forcing-question interrogator pattern matching our cs-* convention
- 6 forcing questions mirroring Matt's 6 review-checklist items
- Routes to validators + karpathy-coder gate + attribution check
Karpathy-coder validation (full sweep):
- complexity_checker: 100/100 across all 3 tools (0 findings)
- assumption_linter: CLEAN on all 3 tools
- All 3 tools: PASS text + PASS JSON output
- All 4 references cite >= 7 authoritative sources (range 7-8)
Self-validation note: this skill's own SKILL.md is 141 lines (over Matt's
100-line ceiling) because it preserves Matt's full content verbatim + adds
attribution + tooling references. The structure_validator + checklist_runner
correctly WARN on this — documented in progressive_disclosure_principles.md
as the wrapper-derived exception. README.md absorbs the attribution overhead
so SKILL.md stays close to Matt's original size.
12 files, 1,689 insertions. License: MIT (matching Matt's upstream).
https://claude.ai/code/session_01VFreMf7XLBqMgjsrG4wSYe
Stream A Phase 1 — Plugin 2 of 3 (compliance OS MVP).
Three stdlib Python tools at the Article level:
- ai_system_risk_classifier.py: Article 5 prohibitions check, then
Article 6 + Annex III, then Article 6(3) carve-out test (overridden by
profiling), then Article 50 transparency, then minimal-risk default.
GPAI detection + Article 51 10^25 FLOPs systemic-risk threshold.
- conformity_assessment_planner.py: Article 43 Module A vs Module H routing
(biometrics -> Module H by default); Annex IV 8-item technical
documentation checklist with ISO 42001/27001 reuse map.
- ai_act_obligation_tracker.py: per-role (provider/deployer/importer/
distributor/auth-rep) obligation matrix with Article 113 phasing
deadlines (2 Feb 2025 / 2 Aug 2025 / 2 Aug 2026 / 2 Aug 2027).
Verified per Phase 1 success criteria: emotion-recognition-in-workplace
classified as prohibited (Article 5(1)(f)); CV-screening as high-risk
(Annex III §4); chatbot as limited-risk (Article 50); spam filter as
minimal-risk.
Four references each citing 5+ authoritative sources (the Regulation,
EDPB Opinion 28/2024, Commission Feb 2025 Guidelines, ENISA, IAPP Tracker,
CEN-CENELEC JTC 21, BSI, NIST AI 600-1):
- eu_ai_act_titles.md: Titles I-XII Article-by-Article walkthrough
- high_risk_systems_annex_iii.md: 8 categories + Article 6(3) decision tree
- gpai_obligations.md: Articles 51-55 + Annex XI-XIII + Code of Practice
- cross_framework_mapping_ai_act.md: AI Act <-> ISO 42001 <-> NIST AI RMF
<-> GDPR cross-walk with Article 17(1) item-by-item mapping
Dual-published: standalone plugin (ra-qm-team/compliance-team-eu-ai-act/) +
mirror under ra-qm-team/skills/eu-ai-act-specialist/.
Karpathy gate: complexity_checker 100/100 (0 findings).
https://claude.ai/code/session_01VFreMf7XLBqMgjsrG4wSYe
Two small polish tasks ahead of any future Pages deploy.
1. Add /cs:* command nav entries (22 new entries)
The 21 c-level-agents-* sub-skill pages now exist (since #632) but weren't
surfaced in mkdocs.yml sidebar nav. Added a "Founder-Mode Commands" nested
section under C-Level Advisory with:
- c-level-agents index
- 10 forcing-question reviews (/cs:cfo-review through /cs:vpe-review)
- 5 strategic sprint pipeline commands (brief/boardroom/decide/execute/post-mortem)
- 4 meta+safety commands (founder-mode/onboard/cross-eval/freeze)
- /cs:office-hours
2. Clear 33 mkdocs INFO warnings
mkdocs build was emitting 33 INFO-level warnings during the docs deploy.
Pre-existing noise; not regressions. Three categories:
a) 27 unrecognized-link warnings: relative links like `[Skills](skills/)`
that mkdocs flags because the path doesn't end in .md. Fix: added
explicit `index.md` suffix in 3 manual doc files.
- docs/index.md: 15 links
- docs/skills/index.md: 11 links
- docs/custom-gpts.md: 1 link
b) 2 anchor warnings in scrum-master TOC: links pointed to
`#analysis-tools--usage` and `#key-metrics--targets` (double hyphen
from ampersand) but mkdocs Material's slugify produces single-hyphen
slugs. Fix: changed to `#analysis-tools-usage` and `#key-metrics-targets`.
c) 4 anchor warnings in senior-computer-vision + senior-data-engineer TOCs:
links pointed to non-existent sections.
- senior-computer-vision: `#common-commands` TOC entry — no such heading
anywhere; removed the entry.
- senior-data-engineer: 3 sub-bullets pointing to `#workflow-1-...`,
`#workflow-2-...`, `#workflow-3-...` — no such headings (only a
parent `## Workflows`); removed the sub-bullets.
Verification:
- mkdocs build now emits 0 INFO warnings
- karpathy diff_surgeon: 0 findings on staged diff
- All 22 new nav entries verified to point to existing HTML pages
- generate-docs.py re-run picked up the upstream SKILL.md fixes; docs/skills/
now matches sources
10 files changed, +54/-39. After the next dev->main release, the Pages
deploy will have:
- Cleaner build output (no INFO noise)
- Fully discoverable /cs:* command pages in the sidebar nav
https://claude.ai/code/session_012WtZMm5NJHqkYoRqA9fHMN
generate-docs.py had a longstanding bug: the rendering loop only iterated
top-level skills and only rendered their direct children. Sub-skills whose
parent is a plugin folder (not a top-level skill at <domain>/skills/<name>/)
were silently dropped.
Affected plugins (standalone-only, no bundled mirror at <domain>/skills/):
- executive-mentor (1 index + 5 sub-skills)
- agenthub (1 index + 7 sub-skills)
- autoresearch-agent (1 index + 5 sub-skills)
- playwright-pro (1 index + 9 sub-skills)
- self-improving-agent (1 index + 5 sub-skills)
- c-level-agents (1 index + 17 sub-skills — the new /cs:* commands)
- llm-wiki (1 index + sub-skills)
- behuman, code-tour, demo-video, helm-chart-builder, karpathy-coder,
llm-cost-optimizer, prompt-governance, statistical-analyst, terraform-patterns,
data-quality-auditor, docker-development (single-skill plugins)
Total: 79 sub-skills + 12 plugin-index skills = 91 pages were being dropped.
(Some plugins like behuman are single-skill so only their index is dropped.)
The bug: rendering loop at line 414 only handled `for skill in top_level`,
then for each top-level found `children = [s for s in sub_skills if
s["parent"] == skill["name"]]`. Plugins where the SKILL.md lives only at
<plugin>/skills/<plugin>/SKILL.md don't appear in top_level (their detection
puts them in sub_skills with parent=themselves), so their children were
orphaned.
The fix: after the existing top-level loop, render orphan sub-skills grouped
by their plugin parent. Index sub-skill (named same as parent) renders as
<parent>.md; other children render as <parent>-<child>.md. This matches the
URL convention already in use (e.g., executive-mentor-challenge.md), so
existing SEO equity is preserved.
Result: skill pages generated 193 → 272 (+79 recovered). Total docs pages
280 → 359. mkdocs build succeeds.
Verified:
- All 12 previously-dropped plugins render their index page
- All 79 previously-dropped sub-skills render their detail pages
- URL convention preserved (executive-mentor-challenge.md, agenthub-board.md,
playwright-pro-coverage.md, etc.)
- karpathy diff_surgeon: 0 findings
After dev → main release: GitHub Pages redeploys with the recovered 79 pages.
The docs site finally has 1:1 correspondence between SKILL.md files in the
repo and pages on the site.
https://claude.ai/code/session_012WtZMm5NJHqkYoRqA9fHMN
