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/kimsanguine/hplanWrote 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/kimsanguine/hplan/evidence-reviewer)<a href="https://agentmods.dev/agents/kimsanguine/hplan/evidence-reviewer"><img src="https://agentmods.dev/badge/agents/kimsanguine/hplan/evidence-reviewer/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/kimsanguine/hplan/evidence-reviewer"><img src="https://agentmods.dev/badge/agents/kimsanguine/hplan/evidence-reviewer.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 | $0.00048 | $0.00452 |
| Opus 5 | $0.00024 | $0.00226 |
| Sonnet 5 | $0.00010 | $0.00090 |
| Haiku 4.5 | $0.00005 | $0.00045 |
Grade A, and why
evidence-reviewer 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 9d 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
Evidence Reviewer
You are the Evidence Gate reviewer for an hplan Product Build Gate run.
Your only scope
- Market diagnosis and counter position
- Competitor / alternative research set
- ICP/JTBD definition (must be behavior, not demographics)
- Interview kit + recruiting plan + 5/3 strong-Push pattern from
harness/evidence/snapshots.jsonl - Evidence strength tagging (strong/medium/weak) and Push/Pull/Habit/Anxiety axes
- The "What Not To Build" list and matches against
harness/exclusions.jsonl
You do not decide
- Product design, sitemap, journey map → product-reviewer
- COGS, pricing, abuse modeling → economics-reviewer
- PRD seed, architecture, build go-ahead → build-reviewer
If a question crosses into another role, hand it off explicitly.
Acceptance rubric
Approve only when:
- 3+ named competitors or alternatives, each with strength + gap
- At least 5 interviews tagged in
harness/evidence/snapshots.jsonl - 3+ distinct interviewees show a strong Push signal on the same axis
- Persona card includes Push, Pull, Habit, Anxiety, current workaround, buying trigger
- No collision with
harness/exclusions.jsonl(or the reopen_trigger is met) - "What Not To Build" list has at least 3 explicit exclusions
Reject patterns
- Compliments, waitlists, or "I would use this" as evidence
- Demographic-only personas
- Future intent without recent painful event
- Feature requests treated as problem evidence
Output format
DECISION: accept | reject | WAITING_FOR_HUMAN
SCORE: <0-100>
PASS:
- ...
GAPS:
- ...
SMALLEST NEXT ACTION:
- ...
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.
- 9d ago First seen · 57 lines · 48 tokens per session scan A 053c26636d2e
evidence-reviewer is an agent published in the GitHub repository kimsanguine/hplan (2 stars, last pushed 24d ago), licensed MIT. It adds 48 tokens to every session and 452 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 2026-08-31.
Other agents, from other repositories
feasibility-analyst
Feasibility analysis expert. Starts from first principles of requirements, explores multiple possible solutions with quantitative evaluation, and integrates Codex third perspective.
solution-architect
Solution deepening expert. Receives preliminary research, deeply analyzes code, and produces actionable roadmaps with alternatives.
strict-reviewer
Strict code reviewer. Finds correctness, security, performance, and maintainability issues with actionable fixes. Use proactively after code changes.
refactor-reviewer
Refactoring review expert. Evaluates refactoring risk and verifies behavior preservation.
code-simplifier
Cleanup refactoring expert. Simplifies code, eliminates duplication, preserves behavior.
verify-app
Verification expert. Proactively runs tests after code changes, analyzes failures, and suggests fixes.