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 toejough/engram --skill curategit clone --depth 1 https://github.com/toejough/engramWrote 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/toejough/engram/curate)<a href="https://agentmods.dev/skills/toejough/engram/curate"><img src="https://agentmods.dev/badge/skills/toejough/engram/curate/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/toejough/engram/curate"><img src="https://agentmods.dev/badge/skills/toejough/engram/curate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00101 | $0.02700 |
| Opus 5.5 | $0.00040 | $0.01080 |
| Sonnet 5.5 | $0.00020 | $0.00540 |
| Haiku 4.5 | $0.00010 | $0.00270 |
Grade A, and why
curate 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 16d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Curate — Judge Pending Offers Against the Host Vault
An offer (a served engram learn from a child, or a parent note pulled down by engram activate)
lands as a pending offer: a real note file, marked pending: true, that hasn't yet been
reviewed against the vault's existing (non-pending) notes. Curation is that review — the same
agent-judged covered/near/absent reasoning recall's Step 2.5 performs against query candidates,
applied instead to a pending offer against the host vault's existing notes.
Host-local only, on your own initiative. engram serve's only job on an offer is stamp the
declared identity, persist the pending marker (or update the same origin's pending offer in place),
respond; a pull-down's only job is fetch and persist the pending copy — judgment happens later, off
the request path, never synchronously inside the HTTP request that created the offer. Invoke this
skill reactively, whenever you notice one of the three surfacing signals (query payload flag, update
notice, write-path nudge), or whenever explicitly asked to curate.
Special Case — Pending Skill Runbook Notes
A pending runbook note that carries a skill_hash field is a skill's registration offer, not a
served write. Handle it separately from regular pending offers — never judge it covered/near/absent,
never discard it, and always keep it in the vault.
For new notes (no runbook fields yet): Author its situation, done_when, triggers, and
red_flags from the skill's body:
situation: when would an agent reach for this skill (retrieval-shaped phrasing, e.g. "reviewing code for style violations")done_when: the observable end state (e.g. "all flagged issues fixed or documented")triggers: literal user phrasings that should fire it (e.g. "code review", "style check"; may be empty)red_flags: the skill's key failure modes — aim for the 1200-byteengram querypreview budget (rendered YAML bytes); never drop a valid red flag to fit
Amend the note: engram amend --target <basename> --situation="<text>" --done-when="<text>" --red-flag="<text>" --trigger="<phrase>" (repeat --trigger and --red-flag for multiple entries). A free-text flag value (for example --situation, --source, --subject, --behavior) must be written as --flag="value" — the quote touching the =, no space — because a value beginning with - is otherwise misread as a new flag and the command fails. Then clear the marker: engram amend --target <basename> --clear-pending (a skill note has no xid, so
engram show prints no # exchange_hash line and there is no --expect-hash to pass).
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.
- 16d ago Changed 06a8c86096fd
- 17d ago Changed · +2 lines 786ac45ef882
- 20d ago Changed · +32 lines · +2 tokens per session fc6443df5160
- 23d ago Changed · +19 lines 67b699e669fb
- 1mo ago First seen · 84 lines · 99 tokens per session scan A 692ec5f5be46
curate is a skill published in the GitHub repository toejough/engram (8 stars, last pushed yesterday), licensed Apache-2.0. It adds 101 tokens to every session and 2,700 once invoked, about $0.0004 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.
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