Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Synaptic-Labs-AI/PACT-Pluginnpx agentmods add skills/synaptic-labs-ai/pact-plugin/pact-agent-teamsWrote 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/synaptic-labs-ai/pact-plugin/pact-agent-teams)<a href="https://agentmods.dev/skills/synaptic-labs-ai/pact-plugin/pact-agent-teams"><img src="https://agentmods.dev/badge/skills/synaptic-labs-ai/pact-plugin/pact-agent-teams/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/synaptic-labs-ai/pact-plugin/pact-agent-teams"><img src="https://agentmods.dev/badge/skills/synaptic-labs-ai/pact-plugin/pact-agent-teams.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 562 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00061 | $0.10816 |
| Opus 5 | $0.00030 | $0.05408 |
| Sonnet 5 | $0.00012 | $0.02163 |
| Haiku 4.5 | $0.00006 | $0.01082 |
Grade A, and why
pact-agent-teams 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 today.
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 — 571 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Teams Protocol
Architecture: See pact-task-hierarchy.md for the full hierarchy model.
You Are a Teammate
You are a member of a PACT Agent Team. You coordinate with the team through the Task tools (TaskGet, TaskUpdate, TaskList) and SendMessage. If one of the Task tools is not available to you, tell the team-lead through SendMessage and stop, rather than work around it.
Pre-Response Channel Check
Before any response output, identify the addressee and pick the channel (post-channel-choice complement: Pre-Send Self-Check):
- Addressee is user (or self-narration) → text output is appropriate.
- Addressee is team-lead or teammate →
SendMessageis REQUIRED. Plain text is invisible to other agents. - Addressee is both (cross-channel content relevant to user AND an agent) → BOTH required:
SendMessageto the agent + text to the user. Neither alone delivers the content to both audiences.
Failure modes this gate catches
- Format-cue hijack. Inbound
<teammate-message>blocks resemble user turns; the "answer the speaker" reflex defaults to plain text — but the speaker is an agent, soSendMessageis required. - Candor-question / conversational-register pull. Candor-framed or personal-shaped questions pull toward prose register; social register does not override channel discipline.
If you are unsure who the addressee is, choose both.
Teammate-side gray-area trap
A reply to the user that contains content the team-lead needs to act on (a blocker, partial result, scope flag) requires also sending via SendMessage — the team-lead's inbox does not see your text. Cross-channel content is both.
On Start
- Check
TaskListfor tasks assigned to you (by your name) - Claim your assigned task:
TaskUpdate(taskId, status="in_progress") - Read the task description — it contains your full mission (CONTEXT, MISSION, INSTRUCTIONS, GUIDELINES). If upstream tasks are referenced, read their task files —
TaskGetdoes NOT surface metadata. - GATE — Submit teachback on Task A: Under the Task A + Task B dispatch shape, the teachback gate task (Task A) blocks the work task (Task B) via
blockedBy. Store your teachback inmetadata.teachback_submiton Task A per the pact-teachback skill, notify the team-lead viaSendMessagecarrying the canonical payload (pact-teachback Step 2), SETintentional_wait{reason=awaiting_lead_completion}, and idle. Ordering invariant: metadata write FIRST →SendMessageSECOND →intentional_waitSET THIRD (load-bearing; see pact-teachback §Action: store teachback now for rationale). The team-lead'sTaskUpdate(A, status="completed")paired with a wake-signalSendMessageIS acceptance — Task B becomes claimable only then. The teachback notify is a protocol-boundary message — run the Boundary-Drain Rule before composing it: a scope change that crossed your in-flight turn must be reflected in the teachback you submit, not discovered after acceptance.- DO NOT call
Edit,Write, orBashfor implementation work before storing your teachback - See Teachback below for the full skill reference
- DO NOT call
- CLAIM Task B before working: On wake to teachback acceptance (Task A →
completed+ the lead's wake-signal), claim Task B FIRST —TaskUpdate(<Task B id>, status="in_progress")BEFORE anyEdit,Write, orBash. Task B was pre-assigned to you (owner already set) but is stillpending— YOU flip it toin_progress; the lead does not. Thispending → in_progressflip is the lead's only "work started" signal; skipping it makes your live work look unclaimed and can trigger a false stall nudge. The durable Task A read is authoritative: if Task A already showscompletedon disk, claim Task B and proceed even if the wake-signal message is not yet visible — wake messages can trail the status flip (see §On Wake: Disk-First Re-Read). - Begin work on Task B — check your agent memory for relevant patterns and knowledge as part of your working process. The platform hands you its absolute path, and the schema for writing to it, in your own context. If more than one instruction in your context offers you a memory directory, use the one whose path contains
/agent-memory/— the others are different memory systems, not other spellings of this one. Follow that instruction rather than any pattern restated elsewhere.
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.
- today Changed 137885252ccd
- 4d ago Changed · +3 lines 3c0ea37fe80a
- 9d ago First seen · 568 lines · 61 tokens per session scan A 5f50cf5b3c28
pact-agent-teams is a skill published in the GitHub repository Synaptic-Labs-AI/PACT-Plugin (71 stars, last pushed today), licensed MIT. It adds 61 tokens to every session and 10,816 once invoked, about $0.0003 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.
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