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 LWTlong/aida --skill aida-recallgit clone --depth 1 https://github.com/LWTlong/aidaWrote 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/lwtlong/aida/aida-recall)<a href="https://agentmods.dev/skills/lwtlong/aida/aida-recall"><img src="https://agentmods.dev/badge/skills/lwtlong/aida/aida-recall.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00041 | $0.00347 |
| Opus 5 | $0.00020 | $0.00173 |
| Sonnet 5 | $0.00008 | $0.00069 |
| Haiku 4.5 | $0.00004 | $0.00035 |
Grade A, and why
aida-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 8d 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.
What it actually says
AIDA Recall
Goal
Surface relevant project decisions from .claude/rules/decisions/. Help the user understand why the code is written the way it is.
Steps
- Call
aida_recallwithaction: "list"to get all decisions. - Filter by relevance to the user's question (by paths, tags, title keywords).
- For the top matches, call
aida_recallwithaction: "get"to show full detail. - Present findings clearly.
Output Format
If the user asked about a specific area (e.g. "what do we know about auth"):
Decisions for
src/auth/**Use JWT refresh rotation (2026-06-14) Context: The previous long-lived refresh tokens couldn't be revoked without a DB hit on every request... Decision: Rotate refresh tokens on every use. Old token invalidated immediately... Consequences: Race condition on parallel requests mitigated by 5s grace window...
If no relevant decisions:
No recorded decisions match this area. Consider running
/aida-remember-branchafter your next feature.
Tips
- Decisions auto-load per file based on
pathsfrontmatter — the user may already have relevant ones in context aida_recall listreturns all decisions sorted by date — useful for a quick "what did we decide recently?"
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.
- 8d ago First seen · 35 lines · 41 tokens per session scan A 601f527cccc5
aida-recall is a skill published in the GitHub repository LWTlong/aida (8 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 347 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 2026-08-31.
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