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/dvnghiem/flowdeck/failure-replay-enginenpx skills add DVNghiem/FlowDeck --skill failure-replay-enginegit clone --depth 1 https://github.com/DVNghiem/FlowDeckWrote 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/dvnghiem/flowdeck/failure-replay-engine)<a href="https://agentmods.dev/skills/dvnghiem/flowdeck/failure-replay-engine"><img src="https://agentmods.dev/badge/skills/dvnghiem/flowdeck/failure-replay-engine.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 5.1 | $0.00031 | $0.00497 |
| Opus 5 | $0.00015 | $0.00249 |
| Sonnet 5 | $0.00006 | $0.00099 |
| Haiku 4.5 | $0.00003 | $0.00050 |
Grade A, and why
failure-replay-engine 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 6d 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
Failure Replay Engine
FlowDeck remembers every failure that has been recorded in this repo. Before making a change, check the failure history for patterns that match your current task.
Failure Types Tracked
| Type | Example |
|---|---|
| reverted_commit | A commit that was rolled back within 48h |
| failed_deployment | A deployment that caused incidents |
| flaky_test | A test that fails intermittently |
| bug_fix | A fix for a production bug |
| build_failure | A change that broke CI |
Workflow
Before Making a Change
- Query
~/.fd-plan/<slug>/.codebase/FAILURES.jsonfor failures matching the affected paths - If a pattern is found with
recurrence_count >= 2, surface a warning - Include the failure context in your planning rationale
After a Failure is Identified
- Record it with the
failure-replaytool - Include: type, description, affected_paths, root_cause, fix_applied, tags
Recording a Failure
{ "action": "record", "entry": {
"id": "auth-jwt-expiry-2024-03",
"type": "bug_fix",
"description": "JWT tokens expired before refreshing, locking out users",
"affected_paths": ["src/services/auth.ts", "src/middleware/validate-token.ts"],
"root_cause": "Clock skew between services caused premature expiry",
"fix_applied": "Added 30s clock skew buffer to expiry check",
"tags": ["auth", "jwt", "timing"]
}}
Querying Before Editing
Always query before touching auth, payment, schema, or async paths:
{ "action": "query", "query": { "path_prefix": "src/services/auth", "limit": 5 } }
Guidance
- Recurring failures (recurrence_count ≥ 3) indicate a systemic issue — escalate to architect
- Mark failures as resolved only after a regression test is green for 2 consecutive CI runs
- Do not delete failure records — they are the repo's institutional memory
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.
- 6d ago First seen · 60 lines · 31 tokens per session scan A 363a6a7bccf7
failure-replay-engine is a skill published in the GitHub repository DVNghiem/FlowDeck (24 stars, last pushed 17d ago), licensed MIT. It adds 31 tokens to every session and 497 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 2026-08-30.
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