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 cobibean/shared-skills-registry-mcp --skill project-memorygit clone --depth 1 https://github.com/cobibean/shared-skills-registry-mcpWrote 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/cobibean/shared-skills-registry-mcp/project-memory)<a href="https://agentmods.dev/skills/cobibean/shared-skills-registry-mcp/project-memory"><img src="https://agentmods.dev/badge/skills/cobibean/shared-skills-registry-mcp/project-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/cobibean/shared-skills-registry-mcp/project-memory"><img src="https://agentmods.dev/badge/skills/cobibean/shared-skills-registry-mcp/project-memory.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00102 | $0.00965 |
| Opus 5 | $0.00051 | $0.00483 |
| Sonnet 5 | $0.00020 | $0.00193 |
| Haiku 4.5 | $0.00010 | $0.00097 |
Grade A, and why
project-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 10d 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Memory
Use project memory to preserve durable project context for humans and future agents.
Project memory is a record of what happened, what was learned, what decisions were made, and what still needs judgment. It is not primarily an agent handoff. Only include handoff or resume instructions when work is incomplete, interrupted, or the user explicitly asks for a handoff.
Project memory lives at:
docs/memory/YYYY-MM-DD/descriptive-slug-memory-YYYY-MM-DD.md
Memory is append-only by default. Create a new file for new work. Do not overwrite, delete, or rewrite prior memory unless the user explicitly asks.
Before Work
For substantial work:
- Find the project root.
- Check whether
docs/memory/exists. - If it exists, list recent memory files:
find docs/memory -type f -name '*.md' | sort | tail -10
- Read the most recent relevant memory files.
- Read any source-of-truth docs referenced by those files when they matter for the task.
- Briefly summarize the relevant context before acting.
If no memory exists, continue normally. Do not create memory at the start unless the user asks.
After Meaningful Work
Create a new memory file when the session produced context that future humans or agents would be annoyed to rediscover.
Use today's local date and create the dated folder if needed:
docs/memory/YYYY-MM-DD/
Use a lowercase descriptive slug:
docs/memory/2026-05-18/auth-flow-memory-2026-05-18.md
Do not write memory for tiny edits, quick answers, routine formatting, or work that leaves no durable decisions, constraints, verification, or next actions.
What To Capture
Capture durable context, not a transcript:
- session summary
- what was learned
- decisions made
- open decisions that still need judgment
- files created or changed
- source-of-truth docs
- commands, tests, builds, screenshots, or checks run
- known constraints, gotchas, and failure modes
- open questions
- recommended next work, when useful
- handoff or resume notes, only when work is incomplete or explicitly handed off
What ships with it
7 files 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.
- references/agent-metadata/openai.yaml 306 B
- references/examples/agent-workspace-memory.md 2.2 KB
- references/examples/design-pass-memory.md 1.7 KB
- references/examples/saas-product-memory.md 1.6 KB
- references/launch-checklist.md 1.2 KB
- references/upstream-source.md 966 B
- templates/memory-template.md 361 B
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.
- 10d ago First seen · 166 lines · 102 tokens per session scan A d2e25e9f63ba
project-memory is a skill published in the GitHub repository cobibean/shared-skills-registry-mcp (7 stars, last pushed 2mo ago), licensed MIT. It adds 102 tokens to every session and 965 once invoked, about $0.0005 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 2026-08-31.
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