Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/aspenkit/aspens/skill-generationnpx skills add aspenkit/aspens --skill skill-generationgit clone --depth 1 https://github.com/aspenkit/aspensWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00030 | $0.02074 |
| Opus 5 | $0.00015 | $0.01037 |
| Sonnet 5 | $0.00006 | $0.00415 |
| Haiku 4.5 | $0.00003 | $0.00207 |
Grade A, and why
skill-generation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are working on aspens' skill generation pipeline — the system that scans repos and uses Claude/Codex CLI to generate skills, hooks, and instructions files.
Domain purpose
aspens doc init orchestrates a multi-step LLM pipeline that turns a scanned repo + import graph into a base skill, per-domain skills, and an instructions file (AGENTS.md or AGENTS.md). Generation is always done in Claude-canonical format and transformed for other targets afterwards. The end product is what other coding agents (and aspens' own hooks) consume to stay grounded in the repo.
Critical files (purpose, not inventory)
src/commands/doc-init.js— the pipeline orchestrator (backend → target → scan → graph → discovery → strategy → mode → generate → validate → transform → write → hooks → recommended extras → config)src/lib/runner.js—runLLM(),loadPrompt(),parseFileOutput(),validateSkillFiles()shared across all LLM-driven commandssrc/lib/skill-writer.js— writes parsed files, generatesskill-rules.json, injects domain bash patterns, mergessettings.jsonsrc/lib/skill-reader.js— parses skill frontmatter, activation patterns, keywords (consumed by skill-writer)src/lib/git-hook.js—installGitHook()/removeGitHook()for post-commit auto-sync (monorepo-aware)src/lib/timeout.js—resolveTimeout()for auto-scaled + user-override timeoutssrc/lib/target.js/src/lib/backend.js/src/lib/target-transform.js— target/backend resolution and Claude→other-target transformsrc/prompts/—doc-init.md,doc-init-domain.md,doc-init-claudemd.md,discover-domains.md,discover-architecture.md, pluspartials/(skill-format, preservation-contract, examples)
Key Concepts
- Pipeline steps: (1) detect backends (2) backend selection (3) target selection (4) scan + graph (5) existing docs discovery check (6) parallel discovery agents (7) strategy (8) mode (9) generate (10) validate (11) transform for non-Claude targets (12) show files + dry-run (13) write (14) install hooks (Claude-only) (15) recommended extras (save-tokens, agents, git hook) (16) persist config to
.aspens.json - Early config persistence: Target/backend config is written to
.aspens.jsonbefore generation starts (after step 4), so a failed generation run still records the user's explicit target/backend choice.saveTokensfrom existing config is preserved. FinalwriteConfigat step 16 addssaveTokensfrom recommended install. --recommendedflag: Skips interactive prompts with smart defaults. Reuses existing target config from.aspens.json. Auto-selects backend from target. Defaults strategy toimprovewhen existing docs found. Auto-picks discovery skip when docs exist. Auto-selects generation mode based on repo size. Also installs save-tokens, bundled Claude agents,dev/gitignore entry, and doc-sync git hook (step 15).- Recommended extras (step 15): When
--recommendedand not--dry-run: callsinstallSaveTokensRecommended()fromsave-tokens.js(if Claude target), copies all bundled agent templates to.claude/agents/(skips existing) viainstallRecommendedClaudeAgents(), addsdev/to.gitignore, installs doc-sync git hook if not present. Summary lines printed after. - Backend before target: Backend selection (step 2) happens before target selection (step 3). If both CLIs available, user picks backend first, then targets. Pre-selects matching target in the multiselect. With
--recommended, backend is inferred from existing target config. - Canonical generation: All prompts receive
CANONICAL_VARS(hardcoded Claude paths:.claude/skills,skill.md,AGENTS.md,.claude). Generation always produces Claude-canonical format regardless of target. Non-Claude targets are produced by post-generation transform viatransformForTarget(). - Incremental writing (chunked mode): When
mode === 'chunked'and not dry-run, generated files are written to disk as each chunk completes instead of waiting until the end. User is prompted to confirm incremental writes before generation starts. Helper functions:validateGeneratedChunk()validates and strips truncated files per chunk;buildOutputFilesForTargets()handles multi-target transform;writeIncrementalOutputs()deduplicates and writes changed files. Tracks written content viaincrementalWriteState(contentsByPath+resultsByPathMaps). When incremental mode is active, post-generation validation/transform/confirm/write steps are skipped (already done per-chunk). parseLLMOutputwith strict single-file fallback: Codex often returns plain markdown without<file>tags.parseLLMOutput(text, allowedPaths, expectedPath)only wraps tagless text as the expected file for true single-file prompts (exactly oneexactFilein allowedPaths, nodirPrefixes). Multi-file prompts require proper<file>tags.- Existing docs reuse: When existing Claude docs are found and strategy is
improve,loadExistingDocsContext()inlines them as## Existing Docs (improve these — preserve hand-written rules...)into the prompt.chooseReuseSourceTarget()decides whether Claude or Codex docs are the source. Supports cross-target reuse (e.g. Claude docs → Codex output). - Domain reuse helpers:
loadReusableDomains()triesloadReusableDomainsFromRules()first (readsskill-rules.json), falls back tofindSkillFiles()withextractKeyFilePatterns()parsing## Key Filesblocks. - Config persistence with target merging: Uses
mergeConfiguredTargets()to avoid dropping previously configured targets.writeConfignow also persistssaveTokensconfig from the recommended install. - Hook installation: Only for targets with
supportsHooks: true(Claude).installHooks()generatesskill-rules.json, copies hook scripts, injects generated domain patterns intopost-tool-use-tracker.shvia# BEGIN/END detect_skill_domainmarkers, mergessettings.json(backs up existing to.bak). - Git hook offer: With
--recommended, git hook is auto-installed (no prompt). Without--recommended, interactive prompt offered. Detection looks for the marker stringaspens doc-sync hook (<rel>)in.git/hooks/post-commit. - Discovery agents: Two LLM calls run in parallel —
discover-domains(hub files + domain clusters) anddiscover-architecture(hub files + ranked + hotspots). Findings are merged intodiscoveryFindingsand parsed; domain-specific slices are injected into each domain prompt as## Discovery Findings for {domain}.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 65 lines · 30 tokens per session scan A db09c275d245
skill-generation is a skill published in the GitHub repository aspenkit/aspens (96 stars, last pushed 16d ago), licensed MIT. It adds 30 tokens to every session and 2,074 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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