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 isolate-the-specific-failure-mode-before-proposing-a-fixgit 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/isolate-the-specific-failure-mode-before-proposing-a-fix)<a href="https://agentmods.dev/skills/zaxbyhub/opencode-swarm/isolate-the-specific-failure-mode-before-proposing-a-fix"><img src="https://agentmods.dev/badge/skills/zaxbyhub/opencode-swarm/isolate-the-specific-failure-mode-before-proposing-a-fix/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/isolate-the-specific-failure-mode-before-proposing-a-fix"><img src="https://agentmods.dev/badge/skills/zaxbyhub/opencode-swarm/isolate-the-specific-failure-mode-before-proposing-a-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00024 | $0.00360 |
| Opus 5 | $0.00012 | $0.00180 |
| Sonnet 5 | $0.00005 | $0.00072 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
isolate-the-specific-failure-mode-before-proposing-a-fix 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 8d 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.
What it actually says
isolate the specific failure mode before proposing a fix
Trigger
- (no explicit trigger metadata; cluster derived from category/tags)
Required Procedure
- isolate the specific failure mode before proposing a fix
- verify each fix addresses exactly one root cause
Forbidden Shortcuts
- (none recorded)
Delegation Template
When delegating a task affected by this skill, include:
SKILLS: file:.opencode/skills/generated/isolate-the-specific-failure-mode-before-proposing-a-fix/SKILL.md
Reviewer Checks
- Verify each required action above appears in the diff.
Test Engineer Checks
- Add or update tests covering the trigger condition and the forbidden shortcut.
Source Knowledge IDs
- a704dc0a-e0a1-42c3-a43e-b0eff135f657 — When a test fails, diagnose each failure mode separately and apply targeted fixes — do not combine unrelated root causes into a single patch.
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.
- 8d ago First seen · 51 lines · 24 tokens per session scan A c3d2573a4180
isolate-the-specific-failure-mode-before-proposing-a-fix is a skill published in the GitHub repository ZaxbyHub/opencode-swarm (467 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 360 once invoked, about $0.0001 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 2026-09-03.
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