Borrowing it
Nothing to install: this file belongs to aspenkit/aspens. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/aspenkit/aspens/main/.agents/skills/codex-support/SKILL.mdgit clone --depth 1 https://github.com/aspenkit/aspensWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aspenkit/aspens/codex-support)<a href="https://agentmods.dev/skills/aspenkit/aspens/codex-support"><img src="https://agentmods.dev/badge/skills/aspenkit/aspens/codex-support/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aspenkit/aspens/codex-support"><img src="https://agentmods.dev/badge/skills/aspenkit/aspens/codex-support.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00024 | $0.01783 |
| Opus 5.5 | $0.00010 | $0.00713 |
| Sonnet 5.5 | $0.00005 | $0.00357 |
| Haiku 4.5 | $0.00002 | $0.00178 |
Grade A, and why
codex-support 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 1mo ago.
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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are working on multi-target output support — the system that lets aspens generate documentation for Claude Code, Codex CLI, or both simultaneously.
Key Concepts
- Target vs Backend: Target = where output goes (claude →
.claude/skills/, codex →.agents/skills/+ directory-scopedAGENTS.md). Backend = which LLM CLI generates the content (claude -porcodex exec). - Target definitions:
TARGETS.claude(centralized) andTARGETS.codex(directory-scoped). Each defines paths and capability flags:supportsHooks,supportsSettings,supportsGraph,supportsSkills,needsActivationSection,needsCodeMapEmbed,supportsMCP. Codex also hasmaxInstructionsBytes(32 KiB) anduserSkillsDir. Codex'sneedsCodeMapEmbedisfalse— condensed cluster/framework data goes into the synthetic.agents/skills/architecture/skill instead of the root AGENTS.md. - Canonical generation: Generation always produces Claude-canonical format first. Prompts always receive
CANONICAL_VARS(hardcoded Claude paths fromdoc-init.js). Transforms run after generation to produce other target formats. - Content transform:
transformForTarget()remaps paths and content. For Codex: base skill → rootAGENTS.md, domain skills → both.agents/skills/{domain}/SKILL.mdand source directoryAGENTS.md.generateCodexSkillReferences()creates.agents/skills/architecture/with code-map data. - Skills section completeness:
collectSkillsForList()(internal) reads every skill from disk undersourceTarget.skillsDirand overlays pending in-flight changes (filespassed to the transform) so the root instructions file's## Skillssection always lists every on-disk skill — not just the subset that changed in this sync. Pending changes win for descriptions; on-disk content survives for unchanged skills. - Instructions file disk fallback:
transformToDirectoryScopedloadsinstructionsFilefrom disk viarepoPathcontext parameter when it's not in the canonical files array (e.g., duringdoc init --strategy skip-existingor incrementaldoc sync). Uses a singlereadFileSyncfromfswrapped in try/catch (no separateexistsSynccheck). - Content sanitization:
sanitizeCodexInstructions()andsanitizeCodexSkill()strip Claude-specific references (hooks, skill-rules.json, Claude Code mentions) from Codex output. sanitizePublishedContent(content, filePath)— Single-chokepoint sanitizer invoked byskill-writer.json every disk write. Always strips## Activationblocks and## Key Filesblocks. Outsidecode-map.md, also strips count-bearing blocks:**Hub files…**,**Domain clusters:**,**High-churn hotspots:**,**Framework entry points…**. Defense in depth — upstream leaks can't reach the user.- Skills-variant stripping:
syncSkillsSection()removes LLM-emitted Skill-section variants (## Skills Reference,## Skills Overview, etc.) before injecting the canonical## Skillslist. Doc-init and doc-sync prompts also forbid such headings. ensureRootKeyFilesSection(content, graphSerialized)— Post-processes root instructions file to guarantee a## Key Filessection with top hub files from the graph.mergeConfiguredTargets(existing, next)— Merges target arrays to avoid dropping previously configured targets during narrower runs. Validates againstTARGETSkeys, deduplicates.getAllowedPaths(targets)— Returns{ dirPrefixes, exactFiles }union across all active targets.- Backend detection:
detectAvailableBackends()checks ifclaudeandcodexCLIs are installed.resolveBackend()picks best match: explicit flag > target match > fallback. - Config persistence:
.aspens.jsonat repo root stores{ targets, backend, version, saveTokens? }.readConfig()returnsnullif missing or if the config is structurally invalid.isValidConfig()validates targets, backend, version, andsaveTokens(viaisValidSaveTokensConfig()). loadConfig(repoPath, { persist })— Reads.aspens.jsonand, if missing, recovers viainferConfig()from on-disk artifacts. Returns{ config, recovered }. Persists inferred config to disk by default unlesspersist: falseis passed.- Feature config (
saveTokens): Optional object in.aspens.jsonvalidated byisValidSaveTokensConfig()— checksenabled(boolean),warnAtTokens/compactAtTokens(positive integers, compact > warn unless either isMAX_SAFE_INTEGER),saveHandoff/sessionRotation(booleans), optionalclaude/codexsub-objects withenabledandmode. writeConfigpreserves feature config:writeConfig()reads existing config and merges —saveTokenspreserved unless explicitly set tonull(intentional removal) orundefined(keep existing). Targets and backend also merge with existing.- Multi-target publish:
doc-syncusespublishFilesForTargets()to generate output for all configured targets from a single LLM run.repoPathis passed through to the transform context. - Codex inference tightened:
inferConfig()only adds'codex'to inferred targets when.codex/config dir or.agents/skills/dir exists. - Conditional architecture ref: Codex
buildCodexSkillRefs()only includes the architecture skill reference when a graph was actually serialized. - Architecture skill is codex-only synthetic: The codex
architectureskill is generated from graph data and has no Claude counterpart by design.logicalKeyForFile()returnsnullfor codexarchitecturepaths soassertTargetParity()won't raise a parity violation for the missing Claude side.
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.
- 1mo ago First seen · 64 lines · 24 tokens per session scan A 6a907b4fb9c3
codex-support is a skill published in the GitHub repository aspenkit/aspens (103 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 1,783 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
do
Work a SpecWeave increment task by task - claim, implement inside its Files, test, commit, done with evidence - alone, unattended or in lanes, then close. Use for "implement", "continue", "auto".
handoff
Hand work to another tool, account or machine and pick it up there, in two words. Use when the user says "hand off", "hand off all", "out of tokens", "switching accounts", "pick up" or "continue".
sw-do
Work a SpecWeave increment task by task - claim, implement inside its Files, test, commit, done with evidence - alone, unattended or in lanes, then close. Use for "implement", "continue", "auto".
sw-handoff
Hand work to another tool, account or machine and pick it up there, in two words. Use when the user says "hand off", "hand off all", "out of tokens", "switching accounts", "pick up" or "continue".
increment
Plan work as a SpecWeave increment - one spec.md with Problem, Scope, numbered ACs, Approach and Tasks - before writing code. Use for "plan a feature", "new increment", "let's build X".
review
Adversarial review of an increment before it ships, by a fresh context or another model family; every finding cites path:line and is re-verified. Use for "review", "qa", "critique this".