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 threadctx-dev/threadctx-mcp --skill team-memorygit clone --depth 1 https://github.com/threadctx-dev/threadctx-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/threadctx-dev/threadctx-mcp/team-memory)<a href="https://agentmods.dev/skills/threadctx-dev/threadctx-mcp/team-memory"><img src="https://agentmods.dev/badge/skills/threadctx-dev/threadctx-mcp/team-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/threadctx-dev/threadctx-mcp/team-memory"><img src="https://agentmods.dev/badge/skills/threadctx-dev/threadctx-mcp/team-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 | $0.00071 | $0.00615 |
| Opus 5.5 | $0.00028 | $0.00246 |
| Sonnet 5.5 | $0.00014 | $0.00123 |
| Haiku 4.5 | $0.00007 | $0.00061 |
Grade A, and why
team-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 2mo 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team memory (threadctx)
threadctx is the team's shared memory. Anything you store can be recalled later by you, by a teammate, or by a teammate's coding agent — across Claude Code, Cursor, and any MCP client. Treat it as writing to a future colleague.
When to query
Call memory_query BEFORE starting work, not after hitting a wall:
- Touching a service, module, or config that looks like it has history
- Fixing a bug that feels like someone may have hit it before
- Making a choice between approaches (a past decision may already settle it)
- Doing anything with deploys, credentials, environments, or CI
Query with a plain-language description of what you're about to do, not keywords: "adding a new billing webhook handler" beats "webhook".
When to write
Call memory_write AFTER:
- Resolving a non-obvious bug (especially one whose symptom pointed the wrong way)
- Making an architectural or tooling decision, including what was rejected and why
- Discovering a gotcha: a flaky step, a misleading error, an undocumented dependency
- Learning something about the environment that isn't in the repo (account quirks, dashboard settings, rate limits)
Don't write things the repo already records (code structure, obvious history) — write the part that ISN'T visible from the code.
How to write a memory a teammate can use
A good memory answers three questions without the reader having your context:
- What happened / what was decided — concrete symptom or decision, with file paths, commands, error text where relevant.
- Why — the root cause or the reasoning, including dead ends ruled out.
- What to do about it — the action a future reader should take or avoid.
Bad: "Fixed the cache bug in the API." Good: "GET /api/v1/memory/list served stale data after PATCH because Next.js Data Cache caches the Neon HTTP driver's fetch() calls even with dynamic='force-dynamic'. Fix: also set fetchCache='force-no-store' on every route using an HTTP DB driver. Verify with a mutate-then-read round-trip against production — the bug only appears on the second read."
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.
- 2mo ago First seen · 59 lines · 71 tokens per session scan A 66946a1b61fa
team-memory is a skill published in the GitHub repository threadctx-dev/threadctx-mcp (1 stars, last pushed 3mo ago), licensed MIT. It adds 71 tokens to every session and 615 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 2026-08-31.
Other skills, from other repositories
knowledge-ingest
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Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
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Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
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LifeOS memory, prior-session recall, and learning capture. USE WHEN capture this learning, document this learning, what did we learn recently, recent learnings, cortex, knowledge, knowledge base, search knowledge, what do we know about, archive, harvest, knowledge status, develop note, add to knowledge, add a people…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…