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 agentmods add skills/coffeecheese/easy-prd-testing/result-aggregationnpx skills add CoffeeCheese/easy-prd-testing --skill result-aggregationgit clone --depth 1 https://github.com/CoffeeCheese/easy-prd-testingWrote 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/coffeecheese/easy-prd-testing/result-aggregation)<a href="https://agentmods.dev/skills/coffeecheese/easy-prd-testing/result-aggregation"><img src="https://agentmods.dev/badge/skills/coffeecheese/easy-prd-testing/result-aggregation.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.00571 |
| Opus 5 | $0.00012 | $0.00285 |
| Sonnet 5 | $0.00005 | $0.00114 |
| Haiku 4.5 | $0.00002 | $0.00057 |
Grade A, and why
result-aggregation 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.
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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Result Aggregation
Goal
Aggregate priority execution records and defect records into root summary files.
Inputs
Read from:
执行结果/P0/
执行结果/P1/
执行结果/P2/
执行结果/P3/
Outputs
Generate or update at the module artifact root:
05-执行记录.md06-缺陷记录.md
Regression Inputs
When present, also read priority-owned regression artifacts:
执行结果/Px/07-回归记录.md执行结果/Px/08-回归缺陷状态.md执行结果/Px/regression-screenshots/执行结果/Px/regression-videos/执行结果/Px/regression-traces/执行结果/Px/regression-scripts/
Root summaries must keep first-run results and regression results distinguishable. Do not overwrite original first-run defects; record regression status as a status update.
Rules
- Root summaries are owned by the main agent.
- Read priority-level
05-执行记录.mdand06-缺陷记录.md. - Treat
通过,失败,阻塞,未测, and待确认as the only valid first-run case statuses. Do not silently map unknown or blank values; flag them for correction in the priority record. - Summarize total, passed, failed, blocked, untested, and pending-confirmation cases from those five statuses. The total must equal their sum.
- Preserve the priority directory boundary and relative evidence paths. Priority agents own
执行结果/Px/; only the main agent writes root05-执行记录.mdand06-缺陷记录.md. - Carry application type, service status and ownership, page-readiness basis, locator type, Console/Network observation, and session/temporary-service cleanup outcomes into the root summary or its priority index. Do not erase a priority-level exception by replacing it with a batch-wide default.
- Keep an actual-result summary separate from diagnostic evidence. Passing cases need a concrete result summary but do not require screenshots or diagnostic artifacts.
- Include Console, Network, video, Trace, and HAR entries only when the execution tool actually produced them. Preserve
未产生（原因）when a priority record reports that material was not generated; never infer evidence from a backend's capabilities. - For failed cases, preserve available failure evidence and any stated reason that expected evidence was not produced. Do not turn a missing optional diagnostic artifact into a successful observation.
- Mark child-agent write boundary violations.
- Do not convert blockers into defects without user confirmation.
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.
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.
- 4d ago First seen · 56 lines · 23 tokens per session scan A e62df0b0ad5f
result-aggregation is a skill published in the GitHub repository CoffeeCheese/easy-prd-testing (2 stars, last pushed 23d ago), licensed MIT. It adds 23 tokens to every session and 571 once invoked, about $0.0001 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.
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