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.
git clone --depth 1 https://github.com/chris-dare-dev/agent-kitWrote 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/commands/chris-dare-dev/agent-kit/memory-sync)<a href="https://agentmods.dev/commands/chris-dare-dev/agent-kit/memory-sync"><img src="https://agentmods.dev/badge/commands/chris-dare-dev/agent-kit/memory-sync/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/commands/chris-dare-dev/agent-kit/memory-sync"><img src="https://agentmods.dev/badge/commands/chris-dare-dev/agent-kit/memory-sync.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00143 | $0.01255 |
| Opus 5.5 | $0.00057 | $0.00502 |
| Sonnet 5.5 | $0.00029 | $0.00251 |
| Haiku 4.5 | $0.00014 | $0.00126 |
Grade A, and why
memory-sync 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/memory-sync — promote a memory lesson to the right tier
Routes one durable learning to a SINGLE canonical tier per the memory-write protocol
(full model: get_reference("agent-memory") → "The wiki tier" + "memory-write protocol").
It does NOT duplicate the same content across tiers — that is the drift trap the
capability-scout internal-adversary warned about. Pick the lowest altitude that fits.
When to use / when NOT to
Use /memory-sync |
Don't |
|---|---|
An agent captured a significant, durable lesson in .claude/agent-memory/<agent>/lessons.md that is useful beyond that one agent/run |
Routine per-run calibration — leave it in lessons.md |
| You want a repo finding visible to other agents/humans (wiki) or made canonical (CLAUDE.md) | Re-recording something already in CLAUDE.md / data/references (dedupe instead) |
The tiers (pick ONE)
wiki(default) — cross-agent, repo-scoped, human-browsable. Written to the repo's Field Notes via the gatedappend_repo_field_noteMCP tool.claude-md— a canonical invariant/decision for the repo. Editplatform/source/<repo>/CLAUDE.md(Decision Records / Pitfalls).references— applies across repos. Editdata/references/*.md(queryable viasearch_platform_knowledge).
Steps (run in the main thread)
- Parse
<repo>, the lesson text, optional--tier/--agent. If--tieris absent, classify: cross-agent-but-repo-scoped →wiki; durable repo invariant →claude-md; cross-repo →references. If genuinely ambiguous, ask the user. - Dedupe FIRST (on-demand, token-safe — never eager-load):
- wiki →
search_repo_wiki({repo, query: <key terms>}) - claude-md → grep
platform/source/<repo>/CLAUDE.md - references →
search_platform_knowledge(<key terms>)If a near-duplicate exists, update it in place (or skip) — do NOT append a duplicate.
- wiki →
- Route + gate:
- wiki: call
append_repo_field_note({repo, entry, agent, dry_run: true})→ show the returned preview + confirm_token to the USER → on explicit approval, call again withconfirm_token+ identical args to write. Sub-agents cannot self-approve; the human approves the preview (External Write Policy). - claude-md: dispatch the
context-curatoragent to draft the CLAUDE.md edit; present the diff; on approval commit and push it directly to the trunk (main). Create an MR only when Chris explicitly requests a review gate. - references: draft the
data/references/edit; present the diff; commit and push it directly to the trunk (main) after authorization. (Per the workspace "Sharing changes" rule, adata/change is only live for the team once it reachesmain.)
- wiki: call
- Back-pointer: annotate the source
lessons.mdentry with the promotion, e.g.(promoted → wiki Field Notes 2026-06-06), so the same lesson is not re-promoted.
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 · 79 lines · 143 tokens per session scan A 4687dec1ed26
memory-sync is a command published in the GitHub repository chris-dare-dev/agent-kit (0 stars, last pushed 2mo ago), licensed MIT. It adds 143 tokens to every session and 1,255 once invoked, about $0.0006 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 2026-08-31.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.