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 M-T-D-N/agentmemory-codex-windows --skill session-historygit clone --depth 1 https://github.com/M-T-D-N/agentmemory-codex-windowsWrote 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/m-t-d-n/agentmemory-codex-windows/session-history)<a href="https://agentmods.dev/skills/m-t-d-n/agentmemory-codex-windows/session-history"><img src="https://agentmods.dev/badge/skills/m-t-d-n/agentmemory-codex-windows/session-history.svg" alt="Measured on agentmods" 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 | $0.00047 | $0.00471 |
| Opus 5 | $0.00023 | $0.00235 |
| Sonnet 5 | $0.00009 | $0.00094 |
| Haiku 4.5 | $0.00005 | $0.00047 |
Grade A, and why
session-history 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 7d 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.
This is a copy
91% identical to session-history — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
The user wants an overview of recent sessions on this project.
Quick start
memory_sessions { "project": "my-project", "limit": 20 }
Expected output:
7f3a9c2 · app · 2026-06-07 09:00 · completed · 14 obs
- decision: Rotate refresh tokens on every use
b21d004 · app · 2026-06-05 14:00 · completed · 9 obs
- code: limit.ts counts per-IP
Why
Only show sessions and observations the tool returned. An empty history is a real answer, never a cue to invent past work.
Workflow
- Resolve the exact registered project and call
memory_sessionswithprojectandlimit: 20for a meaningful window. - Present in reverse chronological order: session id (first 8), project, start time, status.
- For sessions with observations, show the key highlights (type plus title).
- Note the total observation count per session.
- When a session summary exists, surface its title and the key decisions.
Anti-patterns
WRONG: the tool returns two sessions, you describe "several sessions of steady progress" and add ones you remember from the conversation.
RIGHT: show exactly the two sessions returned, each with its real id, status, and observation count.
Checklist
- Every session shown came from the tool response.
- Order is reverse-chronological.
- Per-session observation counts match the response.
- No session or highlight was invented or merged.
See also
recap: same data grouped by date with highlights.handoff: jump straight into the most recent session.recall: search across all sessions by topic.
Troubleshooting
See ../_shared/TROUBLESHOOTING.md if memory_sessions is not available.
What ships with it
1 file 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.
- 7d ago First seen · 63 lines · 47 tokens per session scan A d0f09bfdc8e3
session-history is a skill published in the GitHub repository M-T-D-N/agentmemory-codex-windows (2 stars, last pushed 7d ago), licensed Apache-2.0. It adds 47 tokens to every session and 471 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to session-history, differing in 5 lines, and is treated as a copy.
Other skills, from other repositories
engraphis-memory
Give the agent durable, scoped, explainable memory across sessions and repositories through the Engraphis MCP tools. Use when you learn a convention, decision, bug cause/fix, or user preference worth keeping; when prior context would help before you answer or act (to avoid re-asking or re-deriving); when asked "why is…
slm-recall
Search and retrieve facts, decisions, and past context from SuperLocalMemory. Use when the user asks to recall, find, search, or "what did we decide/say about X". Triggers multi-channel semantic retrieval with reranking; always call before storing anything new.
slm-remember
Capture durable facts, decisions, constraints, and gotchas into SuperLocalMemory. Use when the user says "remember that", "save this decision", "note this constraint", or when a session produces a conclusion worth persisting across sessions. Always recall first to avoid duplicates.
slm-session
Manage SuperLocalMemory session lifecycle — call sessioninit once at the start of every fresh session to load relevant project context and get a sessionid; call closesession when work is meaningfully complete to commit temporal summaries. Correct lifecycle hygiene is what makes SLM's learning loop work.
slm-compress
Compress large text, tool output, or transcripts to reduce context-window usage while keeping the full 1M window intact — call slmcompress(content, mode, reversible, ttlseconds) to shrink content; if the result is lossy a ccrid is returned so you can call slmretrieve(ccrid) later to recover the exact original; always…
slm-status
Health and optimization stats for SuperLocalMemory — call slmoptimizestats() for live compression and cache counters (compressruns, tokenssavedcompress, cacheproxyhits, cacheproxymisses, cachekvhits, cachekvmisses); run slm status [--json] for system state (mode, profile, DB size, fact/entity/edge counts) and slm…