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 write-memorygit 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/write-memory)<a href="https://agentmods.dev/skills/toejough/engram/write-memory"><img src="https://agentmods.dev/badge/skills/toejough/engram/write-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/toejough/engram/write-memory"><img src="https://agentmods.dev/badge/skills/toejough/engram/write-memory.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 | $0.00062 | $0.01876 |
| Opus 5.5 | $0.00025 | $0.00750 |
| Sonnet 5.5 | $0.00012 | $0.00375 |
| Haiku 4.5 | $0.00006 | $0.00188 |
Grade A, and why
write-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 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write Memory — execute a handed-off vault write
You were invoked by a parent skill that already made the judgment (what to write and why). Your job is the write itself: compose, execute, verify, report. Do not re-litigate the parent's judgment; do not decide WHETHER to write.
The handoff contract
The parent provides:
- kind —
fact,feedback,qa, orrunbook - content fields — by kind, per the blocks below
- source — human-readable provenance string
- optional chunk-sources —
<source#anchor>chunk IDs (provenance) - optional tags — categorical
<family>or<family>/<value>strings (kebab-case; fact/feedback/runbook only), e.g.work-kind/rename,tier/cheap,outcome/pass - optional supersedes —
<basename>|<type>|<claim>(types:updates|narrows|refutes), when the parent determined this write corrects a surfaced note - optional position / target — Luhmann placement (
top(default),continuation, orsibling) plus the target note ID (required when position is nottop), when the parent made a disposition decision. Omitted →--position top(today's default), fact/feedback/runbook only. - optional red_flags — task-specific failure modes a general "follow the steps" rule would not catch (runbook only), e.g. "filter-branch on all refs sweeps the backup branch"
- optional triggers — literal cues in a user's message that should surface this runbook first
(runbook only), e.g.
/please, "take this end-to-end"
If a required field is missing, ask for it from the in-session parent context — do not invent content on the parent's behalf.
Compose
kind=feedback:
engram learn feedback --slug <kebab-slug> --position <top|continuation|sibling> [--target <id>] \
--source="<source>" \
--situation="<retrieval-shaped phrase: when does this apply>" \
--behavior="<what was done>" --impact="<why it was wrong/costly>" --action="<what to do instead>" \
[--tag <family>/<value> ...]
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 · +2 lines afad4cb92191
- 26d ago Changed · +6 lines edd3c8b8e01d
- 28d ago Changed · +20 lines 09840c3e5abd
- 1mo ago First seen · 115 lines · 62 tokens per session scan A eba8f55f040e
write-memory is a skill published in the GitHub repository toejough/engram (8 stars, last pushed yesterday), licensed Apache-2.0. It adds 62 tokens to every session and 1,876 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 2026-08-31.
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