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 ZaxbyHub/opencode-swarm --skill baselinegit clone --depth 1 https://github.com/ZaxbyHub/opencode-swarmWrote 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/zaxbyhub/opencode-swarm/baseline)<a href="https://agentmods.dev/skills/zaxbyhub/opencode-swarm/baseline"><img src="https://agentmods.dev/badge/skills/zaxbyhub/opencode-swarm/baseline/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/zaxbyhub/opencode-swarm/baseline"><img src="https://agentmods.dev/badge/skills/zaxbyhub/opencode-swarm/baseline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
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 →
- medium Agent Snooping · line 493 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Excessive Agency · line 510 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00091 | $0.22726 |
| Opus 5.5 | $0.00036 | $0.09090 |
| Sonnet 5.5 | $0.00018 | $0.04545 |
| Haiku 4.5 | $0.00009 | $0.02273 |
Grade A, and why
swarm-pr-review 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 1mo 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 — 1,824 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/swarm-pr-review
Run a structured, high-confidence PR review that maximizes valid findings without flooding the user with unvalidated noise.
The review ladder is:
Scope → obligations → context pack → deterministic signals → parallel explorers → repository-agnostic risk-family coverage (dispatch scaled by depth tier) → independent reviewer validation → critic challenge → grouped synthesis → metrics / knowledge writeback.
Handoff To PR Feedback
Use ../swarm-pr-feedback/SKILL.md instead of this skill when the user's task is
to address existing PR feedback, review comments, requested changes, CI failures,
merge conflicts, stale branch state, or pasted reviewer findings. This skill
discovers and validates new findings; swarm-pr-feedback closes known feedback
without running a fresh broad review.
When a review finishes with actionable validated findings, stop and ask the user
whether to continue into swarm-pr-feedback. Do not auto-dispatch fix work from
PR_REVIEW. Instead, write a handoff artifact — under Profile A,
.swarm/pr-review/<run_id>/feedback-handoff.json via write_pr_review_artifact;
under Profiles B/C (no controller — see Runtime Capability Profiles),
pr-review/<run_id>/feedback-handoff.json inside your session/task workspace,
never under .swarm/ — and include the continuation prompt with that exact
path substituted for <handoff_artifact_path>:
/swarm pr-feedback <PR_URL> continue from <handoff_artifact_path>
<run_id> is a stable identifier for this review run, such as
pr-<number>-<YYYYMMDDHHMMSS> or the existing review artifact run ID when one
was already created. Under Profile A, the exact command is parsed mechanically:
the controller validates the terminal review, the bounded handoff artifact, and
its provenance before atomically replacing the review gate with an unbound
feedback gate. Extra trailing text is not permitted on this continuation form.
Profiles B/C ingest their task-workspace artifact through the skill-managed path.
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.
- 1mo ago First seen · 1,824 lines · 91 tokens per session scan A 1bcee0a5fe06
swarm-pr-review is a skill published in the GitHub repository ZaxbyHub/opencode-swarm (506 stars, last pushed today), licensed MIT. It adds 91 tokens to every session and 22,726 once invoked, about $0.0004 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 2026-09-03.
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