evidence-provenance

evidence-provenance is a skill for Claude Code from rjmurillo/ai-agents. It costs 112 tokens per session (1,697 once invoked), scanned A, original, MIT.

A method for judging whether evidence really comes from an independent source or from the same reasoning process twice. It also records whether a named check was run, failed, was unavailable, or was not run.

In plain words
What is it for?
Use it to assess tests, reviews, reports, and other claims about whether a requirement or implementation was properly verified.
Why use it?
A second file or test is not automatically a second confirmation when both came from the same assumptions. This helps distinguish useful checks from evidence that cannot challenge the original work.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the project-toolkit plugin — 125 skills, 25 commands, 33 agents, 5 hooks shipped together

Good fit Use it to assess tests, reviews, reports, and other claims about whether a requirement or implementation was properly verified.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add rjmurillo/ai-agents
Claude Code
/plugin install project-toolkit

Made for: Claude Code.

Or install project-toolkit, the plugin that ships this one along with the rest of its 125 skills, 25 commands, 33 agents, 5 hooks.

Wrote 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.

agentmods badge for evidence-provenance

README.md
[![agentmods](https://agentmods.dev/badge/skills/rjmurillo/ai-agents/evidence-provenance/github.svg)](https://agentmods.dev/skills/rjmurillo/ai-agents/evidence-provenance)
Your own site
<a href="https://agentmods.dev/skills/rjmurillo/ai-agents/evidence-provenance"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/evidence-provenance/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.

agentmods 80×15 button for evidence-provenance

Your own site · 80×15
<a href="https://agentmods.dev/skills/rjmurillo/ai-agents/evidence-provenance"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/evidence-provenance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 112 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,697 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00112 $0.01697
Opus 5.5 $0.00045 $0.00679
Sonnet 5.5 $0.00022 $0.00339
Haiku 4.5 $0.00011 $0.00170

Measured 4d ago against content hash 6f5eb45b46d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

evidence-provenance 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 4d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/classify_lineage.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.claude/skills/evidence-provenance/SKILL.md · 151 lines

How it starts

The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Evidence Provenance

A second artifact is not a second proof. Count loops, not files.

Owns one invariant: evidence produced by the same reasoning loop as the artifact it validates is one evidentiary loop, unless something outside that loop can falsify it. It does not reject creator-authored tests, require a human reviewer, require several models, or force an expensive or unavailable gate.

Triggers

is this independent evidence, did the reviewer confirm this, closed loop, count the confirmations, which checks actually ran

The invariant

agent reads requirement R
   +--> writes implementation I
   +--> writes new test T from the same reading

I + T  = useful evidence about I
I + T != two independent confirmations of R

Creator tests stay valid. They answer "does I do what I was written to do". They cannot answer "was R read correctly", because both artifacts inherit one reading.

Process

  1. List the claim and the artifact. Name the artifact, its revision, and the premises it was built from (the reading of R, the generator, the fixture source).

  2. Record each piece of evidence with its lineage. The fields and their values are in references/lineage-model.md. Two rules decide most cases:

    • Shared premise or inheritance joins the subject's loop. A reviewer who is handed the implementer's conclusion, or an expected output made by the implementation's generator, is in that loop whatever agent produced it.
    • Lineage you cannot state is lineage you cannot count. An item with no recorded premises is never independent.
  3. Classify. Write the record as JSON and run:

    python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/evidence-provenance/scripts/classify_lineage.py" <record.json>
    

    An item whose bound_to names a different artifact or revision is always rejected (binding-mismatch), not downgraded. Add --promotion when the evidence gates a deployment: every item then also needs a bound_to with artifact, revision, validator, command, and result, or it is rejected as binding-missing.

  4. Read the verdict.

Read the full file on GitHub · 151 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 4d ago First seen · 151 lines · 112 tokens per session scan A 6f5eb45b46d2

Subscribe to this mod's changes

evidence-provenance is a skill published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It adds 112 tokens to every session and 1,697 once invoked, about $0.0004 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 2026-10-14.