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 agentmods add skills/nicknisi/sessions/memorynpx skills add nicknisi/sessions --skill memorygit clone --depth 1 https://github.com/nicknisi/sessionsWhat 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 | $0.00087 | $0.02985 |
| Opus 5 | $0.00044 | $0.01492 |
| Sonnet 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 2d 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.
- 2d ago First seen · 80 lines · 87 tokens per session scan A 707eb1aaf995
memory is a skill published in the GitHub repository nicknisi/sessions (28 stars, last pushed 7d ago), licensed MIT. It adds 87 tokens to every session and 2,985 once invoked, about $0.0004 per session on Opus 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
code-review
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ygrep
IMPORTANT: Try ygrep FIRST for all code and file searches before using Grep, Glob, or Task explore. ygrep uses a pre-built full-text index and returns results in milliseconds. Fall back to built-in tools only if ygrep returns no results.
mikke
ノートフォルダ (Markdown KB) を mikke CLI で検索する。「○○について調べて」「過去のメモは?」「以前どう解決したか」等、過去の知見・記録を引き出す時に起動。最新仕様・時事・バージョン依存の質問では起動しない (Web が真)。.
dowse
Search the user's local files with dowse, a Windows full-text search index (Chinese + English, PDF/txt/md/code). Use this when the user asks you to find something on their disk — a note, a doc, a config, "that file about X" — instead of grepping the whole filesystem.
docingest-docs
Find, search, and read approved documentation snapshots through DocIngest.
session-recall
Recall past AI coding sessions as long-term memory. Use at the START of any non-trivial task, and whenever the user references earlier work ("like we did before", "the X we set up", "last time", "that bug fix"), asks who/when a file was changed, or you need context that predates this conversation. Runs the local…