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 skills add wrg32786/aigent-os --skill skill-recallgit clone --depth 1 https://github.com/wrg32786/aigent-osWrote 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/wrg32786/aigent-os/skill-recall)<a href="https://agentmods.dev/skills/wrg32786/aigent-os/skill-recall"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/skill-recall/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/wrg32786/aigent-os/skill-recall"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/skill-recall.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 | $0.00000 | $0.00553 |
| Opus 5 | $0.00000 | $0.00277 |
| Sonnet 5 | $0.00000 | $0.00111 |
| Haiku 4.5 | $0.00000 | $0.00055 |
Grade A, and why
skill-recall 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 9d 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/skill-recall — Find local skills for current task
When invoked, match the current task against the installed skill taxonomy. Return ranked suggestions or log a gap.
Trigger
/skill-recall or /skill-recall <task description>
Flow
- Parse intent — extract key action words and domain from the task description or current conversation context
- Read taxonomy — load
$AIGENT_VAULT/memory/SKILL_LEDGER.md - Prefix match — match intent keywords against taxonomy paths:
- Direct path match:
research.deepmatches allresearch.deep.*skills - Keyword match: "browser" matches
automation.browser.*, "lyrics" matchesmusic.lyrics.* - Fuzzy domain match: "investigate a bug" matches
research.deep.investigate+strategy.debug.investigate
- Direct path match:
- Check chains — read
$AIGENT_VAULT/memory/SKILL_CHAINS.mdfor prior successful multi-skill sequences with similar objectives - Rank results — prioritize by:
- Exact taxonomy path match (highest)
- Prior chain match (high — proven to work)
- Keyword overlap (medium)
- Domain proximity (lower)
- Output:
- If matches found: return ranked list with skill name, taxonomy path, one-line description, and invocation hint
- If chain match found: suggest the full chain with
→notation - If NO match found: log to
memory/SKILL_GAPS.mdand suggest/skill-hunt
Gap Logging
When no match is found, append a row to memory/SKILL_GAPS.md:
| {today's date} | {task context, 1 line} | {what capability is missing} | — | open |
Then output: "No matching skill found. Gap logged. Run /skill-hunt {gap description} to search externally."
Example
User: /skill-recall transcribe this meeting recording
aigent:
Match: `research.audio.transcriber` — /audio-transcriber
"Transcribe audio files to structured markdown with speaker labels via Whisper"
Invoke: /audio-transcriber <path-to-audio>
Related
- [[memory/SKILL_LEDGER]] — the taxonomy this skill searches
- [[memory/SKILL_GAPS]] — where misses are logged
- [[memory/SKILL_CHAINS]] — prior successful sequences
- [[concepts/Capability Expansion Doctrine]] — the doctrine governing recall + hunt
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.
- 9d ago First seen · 54 lines · 0 tokens per session scan A 4b4e3d2eb450
skill-recall is a skill published in the GitHub repository wrg32786/aigent-os (18 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 553 tokens. 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 2026-09-03.
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