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 nicknisi/sessions --skill memorygit clone --depth 1 https://github.com/nicknisi/sessionsWrote 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/nicknisi/sessions/memory)<a href="https://agentmods.dev/skills/nicknisi/sessions/memory"><img src="https://agentmods.dev/badge/skills/nicknisi/sessions/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/nicknisi/sessions/memory"><img src="https://agentmods.dev/badge/skills/nicknisi/sessions/memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 39 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00087 | $0.02985 |
| Opus 5.5 | $0.00035 | $0.01194 |
| Sonnet 5.5 | $0.00017 | $0.00597 |
| Haiku 4.5 | $0.00009 | $0.00298 |
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 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Turn mined candidate turns into a small set of durable facts worth remembering.
Steps
-
Run the mine.
sessions memory mine --repo <path> --json(omit--repofor the current repo;--allmines every repo in the index; add--since-lastto mine only transcripts that changed since the previous mine, which is what the weekly summary uses). stdout is a JSON array of candidate records; progress goes to stderr. If the command is not found, say so and stop — do not substitute a search. If the array is empty, say there is nothing to triage and stop; never invent candidates. -
Confirm fuzzy paraphrase pairs.
sessions memory report --repo <path> --json(same scoping flags as the mine) returns afuzzyarray: freshly mined clusters that look like paraphrases of an APPROVED memory but scored below the binary's assert threshold. The binary deliberately does not make this judgment — you do. Present each pair (cluster.text~memory.text, with its similarity and session count) and ask confirm/deny, batched with the triage questions in step 7 rather than as a separate interrogation. If the array is empty, move on.- Confirm →
sessions memory merge <memory-id> <cluster-id>— the approved memory is the canonical, the new phrasing folds into it. This is the same write-back as step 8's clustering merge: future mines recognize the phrasing as accounted for, and the pair stops appearing in the report. If merge exits non-zero on an unknown id, runsessions memory mine --repo <path>first and retry — report reads fresh evidence without persisting it, and merge only knows ids the store holds. - Deny →
sessions memory snooze <cluster-id>. Reject would kill the fact itself, which is terminal and wrong when the fact is real; snooze is the suppression that persists the dismissal without a verdict. The report's pipeline drops suppressed clusters before classifying, so the denied pair goes quiet on later runs instead of being re-asked every triage. If snooze exits non-zero on an unknown id, runsessions memory mine --repo <path>first and retry, exactly as with merge. A denied pair resurfaces only the way any snooze does — a later merge folding in a new phrasing after the 30 days pass, which the current mine never produces, so in practice the denial holds until the clustering evidence changes.
- Confirm →
-
Cluster paraphrases. Group candidates whose texts assert the same fact in different words — "use canary as the base branch" and "we branch off canary" are one memory in two phrasings. A cluster's
distinctPhrasingsis the number of distinct member texts. Keep the clearest phrasing as the cluster'stext; the rest are evidence, not separate memory. Byte-identical repeats were already collapsed upstream, so every member you see is genuinely a different wording. -
Read what is already binding.
sessions memory documented --jsonlists every statement an agent working here is already told — the globalCLAUDE.md, a repoCLAUDE.mdorAGENTS.md, and Claude Code's own per-project memory store. Read it before the rubric, because it decides the rubric's first question.These are read, never written. This store complements those surfaces; it does not replace, edit, or override them.
Other agents' stores are candidates, not gospel. If the user asks to pull in what another agent remembers — pi-hermes-memory's store, Claude's CLAUDE.md files — run
sessions memory import --from pi-hermes(orclaude, orall) FIRST, before mining: those facts land in the candidate batch you are about to triage, marked by their lack of session evidence. Triage them through the same rubric below; thereview_agent_memoriesMCP tool previews what would import and flags entries that overlap memories already in the store (similarTo), andget_memory_sourcesinventories what stores exist. A pi-hermes fact scoped to a bare project name arrives unbound — bind it with--scope repo:.when you approve it, or reject it if the project is gone.
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 · 80 lines · 87 tokens per session scan A 707eb1aaf995
memory is a skill published in the GitHub repository nicknisi/sessions (39 stars, last pushed 10d ago), licensed MIT. It adds 87 tokens to every session and 2,985 once invoked, about $0.0003 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.
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