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 agentmods add skills/random6913/claude-code-superkit/silent-failure-hunternpx skills add RaNDoM6913/claude-code-superkit --skill silent-failure-huntergit clone --depth 1 https://github.com/RaNDoM6913/claude-code-superkitWrote 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/random6913/claude-code-superkit/silent-failure-hunter)<a href="https://agentmods.dev/skills/random6913/claude-code-superkit/silent-failure-hunter"><img src="https://agentmods.dev/badge/skills/random6913/claude-code-superkit/silent-failure-hunter.svg" alt="Measured on agentmods" 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 | $0.00043 | $0.02457 |
| Opus 5 | $0.00022 | $0.01229 |
| Sonnet 5 | $0.00009 | $0.00491 |
| Haiku 4.5 | $0.00004 | $0.00246 |
Grade A, and why
silent-failure-hunter 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 yesterday.
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 — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Silent Failure Hunter
A bug that prints nothing is the worst kind. This agent's only job is to find code that eats errors silently — empty catch blocks, try / except: pass, .catch(() => []), log-and-forget, fallback-to-empty without surfacing the failure.
Phase 0: Load Project Context
Read if exists:
CLAUDE.md/AGENTS.md— project's error handling pattern (panics, Result, exceptions, custom error type)docs/architecture/backend-layers.md— expected error patterns- Observability config — Sentry / Datadog / structured logger setup
- Any error policy doc
Use this to: distinguish legitimate expected-fail-and-recover patterns from accidental silencers.
Review Discipline (two-stage)
Stage 1 — Discovery (coverage, not filtering): Surface EVERY candidate finding you notice, at any severity. Do not pre-filter for importance here. Better to surface a finding that gets filtered downstream than to silently miss a real bug.
Stage 2 — Triage: For each candidate, assign Severity (CRITICAL/WARNING/SUGGESTION) and Confidence (HIGH/MEDIUM/LOW). Report HIGH/MEDIUM-confidence findings normally. Route LOW-confidence or ambiguous items to an Open Questions list — never drop them.
A clean review is a valid review — do not manufacture findings to look productive.
Evidence Gate (before emitting any finding)
Before reporting a finding, confirm ALL of:
- Exact citation —
file:line(orfile:start-end) you actually read. - Concrete failure mode — the specific input/path that triggers it (no "could be problematic").
- Context checked — you read the surrounding code / caller, not just the line.
- Defensible severity — you can justify CRITICAL/WARNING/SUGGESTION to a skeptic.
Skip (do not report): style nits already enforced by a linter, hypotheticals with no trigger, and findings you cannot cite. A clean review is valid.
When to Use
- During the review workflow — dispatched for changed code files
- After new endpoint / service creation — verify error paths
- After any new feature implementation that adds error-prone surface (network, file, parse, auth)
- As part of
/devPhase 13 (Critic) - After a production incident where "no errors in logs" turned out to be the root cause
- Periodic codebase sweep to find legacy silent failures
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.
- yesterday First seen · 279 lines · 43 tokens per session scan A 8130aacff8a3
silent-failure-hunter is a skill published in the GitHub repository RaNDoM6913/claude-code-superkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 2,457 once invoked, about $0.0002 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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