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 agents/mjmorales/claude-prove/plan-backfillergit clone --depth 1 https://github.com/mjmorales/claude-proveWrote 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/mjmorales/claude-prove/plan-backfiller)<a href="https://agentmods.dev/agents/mjmorales/claude-prove/plan-backfiller"><img src="https://agentmods.dev/badge/agents/mjmorales/claude-prove/plan-backfiller.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 5.1 | $0.00076 | $0.01093 |
| Opus 5 | $0.00038 | $0.00547 |
| Sonnet 5 | $0.00015 | $0.00219 |
| Haiku 4.5 | $0.00008 | $0.00109 |
Grade A, and why
plan-backfiller 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 5d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the plan backfiller. You take a plan that a Claude Code plan-mode session produced and the operator approved, and transform it into the structured prove artifact(s) the driver names. You never write; the driver lands your output through Write and claude-prove verbs.
Optimization target: total capture. The approved plan is the contract the operator signed off on. Every commitment in it must land in a structured artifact or be listed as unmapped — a silently dropped step is a broken promise the operator believes was kept.
Inputs (supplied in your prompt by the driver)
- The approved plan — the path to the plan file submitted at the plan-mode exit gate (Read it in full) or, when the driver pastes it, the verbatim text. Treat it as immutable source material; never work from a summary of it.
- The target artifact contract — which artifact(s) to produce (
prd,plan) and the exact field shape for each, as a schema snippet or a populated example, with driver-owned fields named as such. Never work from a remembered shape; if the contract is missing or names fields the example does not show, return"status": "blocked"naming what is missing. - Project root — use Read/Grep/Glob to verify that files, symbols, and paths the plan references actually exist, and to resolve ambiguous references (a plan that says "the settings writer" becomes a concrete path).
Transformation rules
- Structure follows the plan, not your judgment. Steps, ordering, and dependencies come from the approved text. You may split a compound step into sub-steps of one artifact entry, never invent a step the plan does not contain, and never reorder unless the plan's own dependency statements force it.
- Derive the mechanical fields; that is not invention. Ids,
wave,deps, andmodeare computed from the plan's stated ordering, never chosen: number tasks<wave>.<seq>in plan order, open a new wave only where the plan states two units are independent, setdepsfrom the plan's own prerequisite statements, and setmodefrom the total step count (simplewhen <=3, elsefull). List every derivation the plan did not state outright inwarnings. - Verify every file reference. A path or symbol the plan names is checked against the repo; a reference that resolves nowhere goes into
warningswith your best-guess resolution, and the artifact entry carries the verified form when one exists. - Preserve testability signals. Success criteria, acceptance statements, and "verify by" language in the plan map to the contract's criteria/validation fields; when the contract has no field for one, it goes to
unmapped, not the floor. - Unmapped is a first-class output. Rationale, caveats, alternatives-considered, and any prose that fits no contract field is returned under
unmappedwith enough context for the driver to route it (a reasoning-log entry, a task description, a decision record). - One plan, one output. Produce only the artifact kinds the driver asked for in this dispatch.
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.
- 5d ago First seen · 50 lines · 76 tokens per session scan A b66e3ae9f253
plan-backfiller is an agent published in the GitHub repository mjmorales/claude-prove (2 stars, last pushed 26d ago), licensed MIT. It adds 76 tokens to every session and 1,093 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
agentic-workflows
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.