agentmemory is a persistent-memory system that lets AI coding agents retain and search information across sessions. It connects with several coding agents and MCP clients, storing knowledge with confidence scoring, lifecycle handling, knowledge graphs, and hybrid search. The catalogue contains agentmemory integrations such as skills, hooks, commands, a plugin, and an MCP component.
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 rohitg00/agentmemory --skill write-agentmemory-skillgit clone --depth 1 https://github.com/rohitg00/agentmemoryWrote 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/rohitg00/agentmemory/write-agentmemory-skill)<a href="https://agentmods.dev/skills/rohitg00/agentmemory/write-agentmemory-skill"><img src="https://agentmods.dev/badge/skills/rohitg00/agentmemory/write-agentmemory-skill/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/rohitg00/agentmemory/write-agentmemory-skill"><img src="https://agentmods.dev/badge/skills/rohitg00/agentmemory/write-agentmemory-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00040 | $0.00536 |
| Opus 5.5 | $0.00016 | $0.00214 |
| Sonnet 5.5 | $0.00008 | $0.00107 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
write-agentmemory-skill 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- write-agentmemory-skill — 100% identical, 3 lines differ
- write-agentmemory-skill — 100% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agentmemory skills follow one tiered format so they stay skimmable, accurate, and current. Match it exactly.
Directory layout
plugin/skills/<name>/
SKILL.md (required, under 100 lines)
REFERENCE.md (optional, dense facts; auto-generate data tables)
EXAMPLES.md (optional, worked transcripts)
TROUBLESHOOTING.md (generated support file)
SKILL.md rules
- Frontmatter:
name,description, optionalargument-hint, anduser-invocable. Setuser-invocable: trueonly for skills the user runs as a slash command; reference and knowledge skills arefalse. - Description is two sentences and the only thing the agent sees when deciding to load the skill. Sentence one states the capability. Sentence two starts "Use when" and lists concrete triggers. Keep it distinct from sibling skills, under 1024 chars, third person.
- Body order: Quick start (one concrete example), Why (the governing principle), Workflow (numbered steps with decision gates), Anti-patterns (a WRONG vs RIGHT callout for the top mistake), Checklist, See also (cross-link siblings), Reference or Troubleshooting pointer.
- Stay under 100 lines. Move dense facts to REFERENCE.md and examples to EXAMPLES.md.
- Keep supporting files inside the skill directory so each skill works when installed separately. Link TROUBLESHOOTING.md; the generator copies shared recovery instructions into each skill root.
Keep it current
Facts that exist in source (tool names and parameters, REST endpoints, env vars, connect adapters, hook events) are generated, never hand-typed. Edit the source, then run npm run skills:gen. CI runs npm run skills:check and fails on drift, so generated tables cannot fall behind the code.
Style
No external or competitor product names. No emojis. No em-dashes. No filler. State the thing and stop.
Checklist
- Description has a "Use when" sentence with real triggers.
- SKILL.md is under 100 lines.
- No time-sensitive claims and no duplicated troubleshooting block.
- Concrete example present; generated facts come from the generator.
- Cross-links resolve and go one level deep.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago Changed · +1 lines 5838e514f9b0
- 1mo ago First seen · 41 lines · 40 tokens per session scan A 07f5e9973c86
write-agentmemory-skill is a skill published in the GitHub repository rohitg00/agentmemory (29,595 stars, last pushed today), licensed Apache-2.0. It adds 40 tokens to every session and 536 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
hindsight-local
Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user).
memory-retain
Save what was learned to Hindsight long-term memory. Use when a task finishes, when the user states a fact, decision or preference, and when you discover something a later run or another Bot would need.
last30Days
Resolve "last30Days" to a concrete ISO date range relative to your run time — a rolling 30-day window ending today. Returns inclusive civil dates plus exact UTC instants so you have temporal context without computing dates by hand. Read-only: no writes, no network. Use before a "last 30 days" / trailing-month task…
thisWeek
Resolve "thisWeek" to a concrete ISO date range relative to your run time — this week so far (Monday → today). Returns inclusive civil dates plus exact UTC instants so you have temporal context without computing dates by hand. Read-only: no writes, no network. Use before a week-to-date task (this week's activity…
session-summaries
What the chat right-panel session summary shows, what it costs, and how to make a session summarize well. Load when the user asks about the session summary panel, why a summary looks wrong or empty, or how to turn it on.
relevance-coarse-filter
Cheap, high-recall first-pass filter that removes obvious junk from a detector candidate pool before expensive story-origin research and PR judgment. Decides keep, monitoronly, or reject — never ranks, writes angles, verifies dates, or decides whether to pitch.