Borrowing it
Nothing to install: this file belongs to mtarcure/claude-vibe-squad. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mtarcure/claude-vibe-squad/main/.agents/skills/data-flow-trace/SKILL.mdgit clone --depth 1 https://github.com/mtarcure/claude-vibe-squadWrote 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/mtarcure/claude-vibe-squad/data-flow-trace)<a href="https://agentmods.dev/skills/mtarcure/claude-vibe-squad/data-flow-trace"><img src="https://agentmods.dev/badge/skills/mtarcure/claude-vibe-squad/data-flow-trace.svg" alt="Measured on agentmods" 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 | $0.00071 | $0.00306 |
| Opus 5 | $0.00036 | $0.00153 |
| Sonnet 5 | $0.00014 | $0.00061 |
| Haiku 4.5 | $0.00007 | $0.00031 |
Grade A, and why
data-flow-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 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
Data Flow Trace
Trace sensitive data through collection, storage, processing, sharing, retention, and deletion paths for privacy review.
Inputs
- System boundaries, actors, data stores, processors, and trust zones.
- Data classes, purposes, legal or policy constraints, and retention promises.
- Evidence from code, configuration, schemas, logs, and operator-provided diagrams.
Method
- Enumerate data sources and classify each field by sensitivity and subject.
- Trace every transformation and transfer across trust or jurisdiction boundaries.
- Record purpose, access principal, encryption state, retention, and deletion behavior at each hop.
- Mark inferred edges separately and identify the evidence needed to confirm them.
- Compare observed flows with stated notice, consent, minimization, and deletion commitments.
Acceptance
- Every source has a terminal store, processor, recipient, or explicit unknown edge.
- Cross-boundary transfers identify sender, receiver, protocol, and protection state.
- Retention and deletion paths are included, not just collection and use.
- Findings distinguish verified evidence from assumptions and rank remediation by exposure.
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 · 31 lines · 0 tokens per session scan A 9f2506781366
data-flow-trace is a skill published in the GitHub repository mtarcure/claude-vibe-squad (109 stars, last pushed 3d ago), licensed MIT. It adds 71 tokens to every session and 306 once invoked, about $0.0004 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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