AgentRecall: Instructions file for Claude Code

CLAUDE.md

AgentRecall CLAUDE.md is an instructions file for Claude Code from AkbarDizaji/AgentRecall. It costs 4,625 tokens per session, scanned A, original, MIT.

Repository instructions for AgentRecall, a memory system that helps an agent decide which conversation information is worth saving for later.

In plain words
What is it for?
Use them when deciding whether to store or skip conversation details and when handling AgentRecall's capture and finalization process.
Why use it?
They prevent memory from being saved based only on keywords and require an explicit judgment when a turn may contain reusable information.

Instructions file for Claude Code

Written for Claude Code: UserPromptSubmit hook event.

This is AkbarDizaji/AgentRecall's own configuration. It tells Claude Code how to work on AgentRecall itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything AgentRecall configures →

Reuse

Borrowing it

Nothing to install: this file belongs to AkbarDizaji/AgentRecall. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/AkbarDizaji/AgentRecall/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/AkbarDizaji/AgentRecall

Made for: Claude Code.

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 AgentRecall CLAUDE.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/akbardizaji/agentrecall/claude-md.svg)](https://agentmods.dev/instructions/akbardizaji/agentrecall/claude-md)
Your own site
<a href="https://agentmods.dev/instructions/akbardizaji/agentrecall/claude-md"><img src="https://agentmods.dev/badge/instructions/akbardizaji/agentrecall/claude-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 4,625 This file is loaded in full into every session.
When invoked 4,625 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.04625 $0.04625
Opus 5 $0.02312 $0.02312
Sonnet 5 $0.00925 $0.00925
Haiku 4.5 $0.00462 $0.00462

Measured 3d ago against content hash 18318c9fabf6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

AgentRecall CLAUDE.md 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 3d 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.

CLAUDE.md · 411 lines

How it starts

The opening of the file, as written. The whole thing — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Memory (AgentRecall)

The agentrecall MCP server holds rules learned from past feedback. Recall and capture are both wired as deterministic hooks: the UserPromptSubmit hook injects the relevant rules automatically, and the Stop hook finalizes each turn through agentrecall finalize-turn. AgentRecall's memory decisions come from a semantic capture judge, not from keyword heuristics: the judge decides whether the turn holds memory-worthy content, and AgentRecall only validates that decision and persists it.

AgentRecall contract: 3 — these instructions were written for that contract: the semantic capture judge, Stop-hook judgment enforcement, and reported rule outcomes. Hooks run the globally installed agentrecall, never this repository's source, so the two can drift apart. Every injected context block names the contract the installed build actually implements, in its heading: ## AgentRecall Technical Context (agentrecall <version>, contract <n>). If that stamp is missing, or names a lower contract than the line above, the installed CLI predates these instructions and cannot accept submit_capture_judgment or rule_outcomes — nothing else reports that, and capture silently stops happening. Run agentrecall doctor and tell the user what it says rather than retrying the calls.

You are that judge. AgentRecall makes no model or network calls of its own — it has no judge to fall back on and never guesses with keywords. So the Stop hook does not decide capture on its own: it enforces that a judgment exists. If a substantive turn reaches Stop with no verdict, AgentRecall declines to let the turn finish and asks you for one; you call submit_capture_judgment, and the turn is finalized from your verdict. A Skip verdict is a complete answer — most turns get one.

Semantic capture judge

Incidental keywords never cause a capture. The judge decides; the system validates and stores. Practical consequences for you:

  • If the user explicitly asks to save/capture/remember a rule, it is saved — even when it is narrow, project-local, stylistic, or a preference. The judge normalizes it into a clean rule.
  • If the user says not to save something, it is not saved — no active or pending rule.
  • A universal constraint becomes a standing rule. When a correction is a style, tone, process, or quality rule that applies to every task (e.g. "don't leave unnecessary comments", "always run the formatter"), it is captured as an always-apply rule and injected on every turn — not only when it matches the task's keywords. Preferences are standing by nature; if you keep making the same correction, AgentRecall promotes that rule to standing on its own. Standing rules are marked [standing] in the summary.
  • Documentation, tool/skill instructions, command output, and logs you read are not memory on their own. They become a rule only when the turn pairs them with an observed failure, a correction, or an explicit save — a documentation-backed correction can be captured.
  • Do not narrate the mechanism. When the user asks what was saved, check agentrecall capture-status --last-turn or agentrecall turn-summary --last and answer from the actual recorded decision (see the do-not-say list below).
  • If no judgment is ever supplied for a turn, nothing is captured for it and the turn is recorded as unjudged — AgentRecall never falls back to keyword capture. "Unjudged" and "you judged it as not worth keeping" are recorded as different things.

Read the full file on GitHub · 411 lines

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. 3d ago Changed · +11 lines · +170 tokens per session 18318c9fabf6
  2. 4d ago Changed · +29 lines · +395 tokens per session a9c0ac0e5b95
  3. 8d ago First seen · 371 lines · 4,060 tokens per session scan A 5336e06f9921

Subscribe to this mod's changes

AgentRecall CLAUDE.md is an instructions file published in the GitHub repository AkbarDizaji/AgentRecall (9 stars, last pushed yesterday), licensed MIT. It adds 4,625 tokens to every session, about $0.0231 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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