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 DVNghiem/FlowDeck --skill decision-tracegit 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/decision-trace)<a href="https://agentmods.dev/skills/dvnghiem/flowdeck/decision-trace"><img src="https://agentmods.dev/badge/skills/dvnghiem/flowdeck/decision-trace/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/dvnghiem/flowdeck/decision-trace"><img src="https://agentmods.dev/badge/skills/dvnghiem/flowdeck/decision-trace.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Excessive Agency · line 201 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 | $0.00029 | $0.01940 |
| Opus 5.5 | $0.00012 | $0.00776 |
| Sonnet 5.5 | $0.00006 | $0.00388 |
| Haiku 4.5 | $0.00003 | $0.00194 |
Grade A, and why
decision-trace 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 2mo 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 — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decision Trace
Every non-trivial edit should be recorded in ~/.fd-plan/<slug>/.codebase/DECISIONS.jsonl. This creates an append-only audit trail that makes code review and debugging faster.
When to Record a Decision
Record when:
- Editing a file that affects behavior (not just formatting/comments)
- Choosing between two or more implementation approaches
- Making an assumption about a requirement
- Fixing a bug or regression
- Changing an API contract or schema
How to Record
Use the decision-trace tool:
{
"action": "record",
"entry": {
"id": "auth-refactor-2024-05-01",
"file_path": "src/services/auth.ts",
"change_type": "edit",
"rationale": "Refactored token validation to use constant-time comparison to prevent timing attacks",
"evidence": [
"OWASP: timing attacks on string comparison",
"Prior failure: auth-timing-2024-03 in FAILURES.json"
],
"assumptions": [
"Token format remains base64-encoded JWT",
"Redis cache is available for token blacklist"
],
"alternatives_considered": [
"Keep string comparison (rejected: timing attack risk)",
"Move validation to edge (rejected: adds latency)"
],
"risk_level": "medium",
"agent": "backend-coder"
}
}
Automatic Recording
The decision-trace-hook auto-records a minimal entry for every write/edit. The full entry (with rationale, evidence, assumptions) should be added by the agent explicitly using the tool above.
Querying Decisions
// Get all decisions for a file
{ "action": "get_for_file", "file_path": "src/services/auth.ts" }
// Get all high-risk decisions
{ "action": "query", "query": { "risk_level": "high", "limit": 10 } }
Decision Evolution
Decisions are not static. They change as requirements shift, new evidence appears, or better alternatives emerge. Track the full lifecycle:
alternatives_considered
List every option evaluated and why it was rejected or accepted. This prevents re-litigating old choices.
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.
- 2mo ago First seen · 210 lines · 29 tokens per session scan A 6015902f3296
decision-trace is a skill published in the GitHub repository DVNghiem/FlowDeck (39 stars, last pushed 2mo ago), licensed MIT. It adds 29 tokens to every session and 1,940 once invoked, about $0.0001 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 2026-08-30.
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