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 JinPLu/Teamwork --skill teamwork-collaborategit clone --depth 1 https://github.com/JinPLu/TeamworkWrote 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/jinplu/teamwork/teamwork-collaborate)<a href="https://agentmods.dev/skills/jinplu/teamwork/teamwork-collaborate"><img src="https://agentmods.dev/badge/skills/jinplu/teamwork/teamwork-collaborate/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/jinplu/teamwork/teamwork-collaborate"><img src="https://agentmods.dev/badge/skills/jinplu/teamwork/teamwork-collaborate.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 | $0.00049 | $0.00908 |
| Opus 5.5 | $0.00020 | $0.00363 |
| Sonnet 5.5 | $0.00010 | $0.00182 |
| Haiku 4.5 | $0.00005 | $0.00091 |
Grade A, and why
teamwork-collaborate 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Teamwork Collaborate
Root owns the conversation. Keep clear work native and activate Collaborate when the user wants to think together, when an unresolved preference would materially change the result, or when unclear intent needs guided clarification.
Method
- Rebuild the full decision surface first: the final goal, prior work on this question, settled constraints and recorded rejections, and the unknowns that would change the goal, direction, or acceptance. Start from facts, constraints, and the goal. Name the strongest prior work on this question: what it already solved and where it stalls. Do not invent a stack from zero. Map the discussion from goal to stage to questions with a concise tree or list; use Mermaid when the option space needs that structure.
- A stage is one dependency layer of user-owned decisions. Ask every independent, valuable question for that stage together and defer dependents later; host UI limits are not Teamwork limits.
- Develop only meaningfully different options. For each, explain the main benefit, cost, assumption, and consequence. Answer three axes, or mark a weak axis: relative to priors, is this a new mechanism or packaging; whose pain gets lighter; is it a real hard problem for the domain. Practice first: unobserved local results are not done. Tests on disk are not verification. Practice first forbids claiming an unobserved result; it does not require proxy experiments before an authorized real attempt.
- Resolve discoverable facts directly. Ask the user only for preferences or authority that cannot be discovered. Remaining questions that would not change the next step are not this stage. Use subagents only for bounded evidence gathering or a genuinely independent challenge. Settled user constraints must include recorded rejections and decisions, and the requested return must not change the topic.
- When this turn involves experiment scheduling, GPU or other scarce compute, or
a paper / contribution table slot, follow
references/experiment.md. Otherwise skip Experiment. - Recommend a direction when the evidence distinguishes one. Lead with the claim, then checkable behavior. Define a new term in one sentence. No slogans; do not paper over holes with coinages. Record the user's decision and advance to the next dependent stage. Recorded rejections and decisions are the mainline; research or a subagent return must not restate them as a new question. After research, do not rewrite the question. Quote the user's decision or rejection; do not paraphrase it into a new problem. Do not reopen settled dimensions; update only what the evidence changed. A fluent next step is not convergence. If a new direction is weak on the three axes, improve the anchored problem instead of reopening it.
- End with the decision, unresolved points, and the next authorized action. When the direction is decided and the user authorizes execution, the discussion ends at that real action; do not open a new evidence gate or a new planning door. The next turn on the same subject reads the discussion document's current synthesis first when that document exists.
What ships with it
3 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.
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 · 73 lines · 49 tokens per session scan A 1ddd98d15f5a
teamwork-collaborate is a skill published in the GitHub repository JinPLu/Teamwork (12 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 908 once invoked, about $0.0002 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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