recall

recall is a command for coding agents from naimkatiman/continuous-improvement. It costs 44 tokens per session (464 once invoked), scanned A, original, MIT.

A command that searches records of observations from earlier tool calls in the same project. BM25 is a text-matching method that ranks results by how closely their words match your query.

In plain words
What is it for?
Use it before troubleshooting or making changes when you want to find earlier examples such as permission errors, missing commands, or authentication problems.
Why use it?
It helps the agent check whether a similar problem or fix was seen before, reducing repeated investigation and mistakes. Search is based on matching words, not meaning.

Command

Install

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.

agentmods
npx agentmods add commands/naimkatiman/continuous-improvement/recall
Clone the repo
git clone --depth 1 https://github.com/naimkatiman/continuous-improvement

Wrote 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.

agentmods badge for recall

README.md
[![agentmods](https://agentmods.dev/badge/commands/naimkatiman/continuous-improvement/recall.svg)](https://agentmods.dev/commands/naimkatiman/continuous-improvement/recall)
Your own site
<a href="https://agentmods.dev/commands/naimkatiman/continuous-improvement/recall"><img src="https://agentmods.dev/badge/commands/naimkatiman/continuous-improvement/recall.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 464 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00044 $0.00464
Opus 5 $0.00022 $0.00232
Sonnet 5 $0.00009 $0.00093
Haiku 4.5 $0.00004 $0.00046

Measured 4d ago against content hash ad4a23529711, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 4d 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.

commands/recall.md · 50 lines

What it actually says

/recall — Episodic Search Over Past Sessions

Search this project's observation history for relevant prior activity and return the most relevant past tool calls, ranked.

What it does

Builds an in-memory BM25 index over ~/.claude/instincts/<project-hash>/observations.jsonl and returns the top matches with redacted snippets, relevance scores, and timestamps. Backed by the ci_recall MCP tool (expert mode) and the recall skill.

How to invoke

ci_recall query="permission denied push"     # top 5 matches
ci_recall query="jq command not found" k=3    # cap results
ci_recall query="auth login" since=7d          # only the last 7 days

since accepts an ISO timestamp or a relative window: 7d, 24h, 30m.

Output shape

## Recall: "permission denied push"

2 match(es), most relevant first:

- [2026-05-20T10:00:00Z] **Bash** (score 3.41)
  …git push origin main  Permission denied: harness blocked direct push to main…
- ...

Privacy

Snippets are passed through a secret redactor (AWS keys, JWT-shaped triplets, bearer tokens, KEY/SECRET/TOKEN/PASSWORD assignments, long hex strings) before display.

Notes

  • Lexical, not semantic — search with the vocabulary that actually appeared in the tool calls; try several phrasings if the first returns nothing.
  • Searches the full captured history, not just the recent window.

Pairs with

  • recall skill — the discipline this command runs.
  • continuous-improvement (core SKILL.md, Law 1 — Research Before Executing).
  • gateguard — recall a past failure before clearing a high-risk action.
Changes

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.

  1. 4d ago First seen · 50 lines · 44 tokens per session scan A ad4a23529711

Subscribe to this mod's changes

recall is a command published in the GitHub repository naimkatiman/continuous-improvement (7 stars, last pushed 9d ago), licensed MIT. It adds 44 tokens to every session and 464 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.