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 boshu2/agentops --skill memorygit clone --depth 1 https://github.com/boshu2/agentopsWrote 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/boshu2/agentops/memory)<a href="https://agentmods.dev/skills/boshu2/agentops/memory"><img src="https://agentmods.dev/badge/skills/boshu2/agentops/memory/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/boshu2/agentops/memory"><img src="https://agentmods.dev/badge/skills/boshu2/agentops/memory.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 | $0.00031 | $0.01637 |
| Opus 5.5 | $0.00012 | $0.00655 |
| Sonnet 5.5 | $0.00006 | $0.00327 |
| Haiku 4.5 | $0.00003 | $0.00164 |
Grade A, and why
memory 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 yesterday.
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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory
Use maintained experience only when it changes an action. Memory is optional: no mandatory recall at RPI entry, lesson at completion, worksheet, page quota or background mining. A trivial edit can proceed directly to implementation.
Rules for any saved lesson or rule
Apply these whenever a request would save or promote a lesson, including a request to turn an incident into a rule for an instruction file:
- Look for an existing entry first. Search the selected
.context/pages, external topic pages or the target instruction file (AGENTS.md,CLAUDE.md, a team rules file). Amend the entry that already covers the behavior; add a new one only when none fits. If the final code, tests, comments or a doc already explain the reasoning, point there rather than save a copy; save only what they cannot show a later reader, such as ruled-out causes, why the fix works and what brings the failure back. Effort, a finished task or a large diff never qualifies a lesson. If nothing qualifies, save nothing and say why. - Size the claim to its evidence. One incident supports a narrow observation scoped to the conditions it actually had. A universal rule needs repeated independent occurrences and later reapplication. When a recurring correction is a mechanical slip that a lint rule, test or hook could catch, propose that check alongside the prose rule or in its place, as Postmortem does for such a miss; a check fails where a rule can only ask.
- State all five fields: applicability, action, support, limits and invalidation.
Use the template below; an entry with no invalidation is incomplete. For an
incident, applicability includes the exact error text or observable symptom,
the words a later search will use. An instruction file such as
AGENTS.mdloads into every session, so its entry is usually one line: the action and when it applies, worded as information rather than an order to read, linking the project.context/page or the doc beside the governed code (never an external-bundle page from a checked-in file) that carries all five fields. A line that only restates what agents already do by default earns no place. - Review before admission. Give the draft inline in your reply unless the
caller named storage outside Git; never write it into the repository before
review. A fresh reviewer who is not the author checks factual support and
disclosure of the exact text, paths and destination before it enters
.context/, an instruction file such asAGENTS.md, or any Git object. Promoting an entry into an instruction file is a separate policy change owned by that file. On an explicit request to remember something, the runtime's own memory store (such as Claude Code auto-memory or Codex memory) is a valid destination; rules 1-3 still apply, and fresh review is owed only when that store is shared or checked in. - Saving proves nothing. Saved pages, retrieval counts and structural checks prove no benefit. Only later work can show that reuse changed an action and helped; keep failed, harmful and no-change results. Until then a saved rule is an untested hypothesis.
What ships with it
7 files 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.
- yesterday Changed · -7 lines 1392a9c422a6
- 4d ago Changed · +4 lines b7e2fa617909
- 5d ago Changed · +13 lines · -1 tokens per session 7aa4929f1725
- 21d ago Changed · -4 lines · -2 tokens per session 519025d58436
- 1mo ago Changed · -22 lines daca35193911
- 1mo ago Changed · +19 lines · +1 tokens per session 0088646b9887
- 1mo ago Changed · +30 lines · -18 tokens per session 6ac12abe5e43
- 1mo ago First seen · 100 lines · 51 tokens per session scan A 04bab7eb12ec
memory is a skill published in the GitHub repository boshu2/agentops (450 stars, last pushed today), licensed Apache-2.0. It adds 31 tokens to every session and 1,637 once invoked, about $0.0001 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 2026-09-09.
Other skills, from other repositories
autolearn
Use when a verified non-trivial fix lands or existing solution docs need refresh. Not for unverified fixes.
history-forget
Use when the user asks to remove a session or note from recall, or to unforget or list exclusions. Not for remote, credential, publish, deploy, or irreversible changes.
history-sync
Use when the user requests memory transfer to or from a named peer. Not for recalling a session: use history-recall. Not for store registration: use history-source-registry.
keep-why-continuous-capture
Use when a non-trivial change lands or is abandoned and its decision, rejected alternatives, and reason must be captured. Not for trivial or corrective changes: those belong in CHANGELOG.
history-notes
Use when the user says remember this or settles one durable fact. Not for remote, credential, publish, deploy, or irreversible changes.
history-source-registry
Use when a coding-agent session store is added or its format drifts, to document its layout, roles, quirks. Not for recalling a session: use history-recall. Not for peer transfer: use history-sync.