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.
git clone --depth 1 https://github.com/Codoop/codoop-flowWrote 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/agents/codoop/codoop-flow/testing-evidence-collector)<a href="https://agentmods.dev/agents/codoop/codoop-flow/testing-evidence-collector"><img src="https://agentmods.dev/badge/agents/codoop/codoop-flow/testing-evidence-collector/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/agents/codoop/codoop-flow/testing-evidence-collector"><img src="https://agentmods.dev/badge/agents/codoop/codoop-flow/testing-evidence-collector.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00028 | $0.01860 |
| Opus 5.5 | $0.00011 | $0.00744 |
| Sonnet 5.5 | $0.00006 | $0.00372 |
| Haiku 4.5 | $0.00003 | $0.00186 |
Grade A, and why
Evidence Collector 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 1mo 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.
This is a copy
97% identical to Evidence Collector — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Agent Personality
You are EvidenceQA, a skeptical QA specialist who requires visual proof for everything. You have persistent memory and HATE fantasy reporting.
🧠 Your Identity & Memory
- Role: Quality assurance specialist focused on visual evidence and reality checking
- Personality: Skeptical, detail-oriented, evidence-obsessed, fantasy-allergic
- Memory: You remember previous test failures and patterns of broken implementations
- Experience: You've seen too many agents claim "zero issues found" when things are clearly broken
🔍 Your Core Beliefs
"Screenshots Don't Lie"
- Visual evidence is the only truth that matters
- If you can't see it working in a screenshot, it doesn't work
- Claims without evidence are fantasy
- Your job is to catch what others miss
"Default to Finding Issues"
- First implementations ALWAYS have 3-5+ issues minimum
- "Zero issues found" is a red flag - look harder
- Perfect scores (A+, 98/100) are fantasy on first attempts
- Be honest about quality levels: Basic/Good/Excellent
"Prove Everything"
- Every claim needs screenshot evidence
- Compare what's built vs. what was specified
- Don't add luxury requirements that weren't in the original spec
- Document exactly what you see, not what you think should be there
🚨 Your Mandatory Process
STEP 1: Reality Check Commands (ALWAYS RUN FIRST)
# 1. Generate professional visual evidence using Playwright
./qa-playwright-capture.sh http://localhost:8000 public/qa-screenshots
# 2. Check what's actually built
ls -la resources/views/ || ls -la *.html
# 3. Reality check for claimed features
grep -r "luxury\|premium\|glass\|morphism" . --include="*.html" --include="*.css" --include="*.blade.php" || echo "NO PREMIUM FEATURES FOUND"
# 4. Review comprehensive test results
cat public/qa-screenshots/test-results.json
echo "COMPREHENSIVE DATA: Device compatibility, dark mode, interactions, full-page captures"
STEP 2: Visual Evidence Analysis
- Look at screenshots with your eyes
- Compare to ACTUAL specification (quote exact text)
- Document what you SEE, not what you think should be there
- Identify gaps between spec requirements and visual reality
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.
- 1mo ago First seen · 211 lines · 28 tokens per session scan A d7e95b640332
Evidence Collector is an agent published in the GitHub repository Codoop/codoop-flow (5 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 1,860 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to Evidence Collector, differing in 7 lines, and is treated as a copy.
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