Borrowing it
Nothing to install: this file belongs to julien777z/agent-sync-action. 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/julien777z/agent-sync-action/main/.agents/skills/grade-plans/SKILL.mdgit clone --depth 1 https://github.com/julien777z/agent-sync-actionWrote 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/julien777z/agent-sync-action/grade-plans)<a href="https://agentmods.dev/skills/julien777z/agent-sync-action/grade-plans"><img src="https://agentmods.dev/badge/skills/julien777z/agent-sync-action/grade-plans/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/skills/julien777z/agent-sync-action/grade-plans"><img src="https://agentmods.dev/badge/skills/julien777z/agent-sync-action/grade-plans.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 | $0.00075 | $0.00872 |
| Opus 5 | $0.00037 | $0.00436 |
| Sonnet 5 | $0.00015 | $0.00174 |
| Haiku 4.5 | $0.00007 | $0.00087 |
Grade A, and why
grade-plans 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- grade-plans — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grade Plans
Compare only the submitted plan text against the supplied goal. Treat model identifiers as reporting labels; never let model reputation affect a score.
Collect Inputs
- Treat everything after
/grade-plansas the goal or original agent prompt. - If no goal is present, ask exactly: “Provide the goal or original agent prompt the two plans should address.” Then wait before collecting plans.
- Ask exactly: “Paste Plan 1 as text and provide the model name or identifier that produced it.”
- Wait. If the response lacks the plan or model identifier, ask only for the missing item.
- Ask exactly: “Paste Plan 2 as text and provide the model name or identifier that produced it.”
- Wait and ask only for any missing item.
- Do not grade until the goal, both plan texts, and both model identifiers are available.
During collection, respond only with the current missing-input question. Do not explain the workflow or describe what should be asked.
Treat plans inside Markdown code fences as ordinary message text. Never call plans attachments.
Grade Plans
Score each criterion from 1–10 using the same evidentiary standard for both plans:
| Criterion | Weight |
|---|---|
| Goal alignment | 20% |
| Correctness and feasibility | 20% |
| Completeness and coverage | 15% |
| Specificity and actionability | 15% |
| Risks, edge cases, and failure handling | 10% |
| Testing and acceptance criteria | 10% |
| Efficiency and scope discipline | 10% |
Calculate each weighted overall score as sum(score × weight) and report it out of 10 to one decimal place. Before scoring, replace the model identifiers internally with neutral labels and freeze every criterion score, weighted total, rationale, verdict, confidence level, and transfer idea from the plan text alone. Attach the submitted model identifiers only after that evaluation is complete. Swapping only the model identifiers must change only the identifiers in the report; all scores and conclusions must remain identical.
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 · 58 lines · 75 tokens per session scan A bef4e39c78d7
grade-plans is a skill published in the GitHub repository julien777z/agent-sync-action (5 stars, last pushed 2d ago), licensed MIT. It adds 75 tokens to every session and 872 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 2026-08-31.
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