plan-execution-loop

A repeatable process for implementing one section of a written development plan, checking the result against its requirements, fixing failures, and checking again.

In plain words
What is it for?
Use it to execute plan slices from docs/plans/*.md with implementation, evidence-based review, fixes, and a required score before moving on.
Why use it?
It prevents a plan from being treated as complete without evidence that every requirement works and keeps work limited to the selected section.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/golid-ai/golid/plan-execution-loop
Clone the repo
git clone --depth 1 https://github.com/golid-ai/golid

Made for: Cursor.

Per session 29 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,888 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00029 $0.01888
Opus 5 $0.00015 $0.00944
Sonnet 5 $0.00006 $0.00378
Haiku 4.5 $0.00003 $0.00189

Measured 2d ago against content hash 6490a45c7972, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

plan-execution-loop 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 2d 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.

.cursor/rules/plan-execution-loop.mdc · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Plan Execution Loop

Thesis: One plan slice at a time — implement, evidence-based audit (≥90/100, file:line proof required), fix, re-audit — then next slice. Parent agent orchestrates; subagents implement and audit.

Invoke when: User says "run the plan", "execute slice X", or points at docs/plans/*.md for implementation.

Per-slice loop (do not skip)

1. IMPLEMENT — Task subagent: read plan slice only; implement; run verification commands; update Progress row
2. AUDIT   — Task subagent (readonly): grade /100 vs slice acceptance with file:line evidence; PASS only if ≥90 and every criterion has proof
3. FIX     — if FAIL: Task subagent applies audit fix list; no scope creep
4. RE-AUDIT — repeat 2–3 until ≥90 with full evidence
5. NEXT SLICE — only after current slice PASS

Subagent prompts must include

  • Exact slice ID and file path to plan section
  • Acceptance criteria from plan (copy verbatim)
  • Verification commands (npm run test:coverage, check_spec_drift.sh, etc.)
  • Forbidden scope (other slices, unrelated refactors)
  • Evidence rule: every deduction needs path:line citation; every PASS criterion needs path:line proof or automatic FAIL
  • Fresh grade (audit dispatches only): grade the artifact as it exists now — start at 100, deduct only for current gaps with path:line proof. Do not reward "improvement since last pass", prior fix lists, or Progress table history. Parent must not anchor with prior scores (see Re-audit below).
  • "Return: grade, PASS/FAIL, evidence table, fix list, files changed, blockers"

Evidence-based audit (mandatory)

Audit subagents grade evidence, not vibes. A numeric score without citations is invalid.

For every deduction — cite path:line (or path:line-line for a range) showing the gap. Example: -5 Scope: backend/internal/handler/foo.go:42 — touches bar.go, outside slice file list.

For every slice acceptance criterion — cite path:line (or command output) proving it is met. If the auditor cannot find proof after reading the diff and running verification commands, that criterion is automatic FAIL regardless of the running score.

Read the full file on GitHub · 146 lines

Changes

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.

  1. 2d ago First seen · 146 lines · 29 tokens per session scan A 6490a45c7972

Subscribe to this mod's changes

plan-execution-loop is a cursor rule published in the GitHub repository golid-ai/golid (40 stars, last pushed 2mo ago), licensed MIT. It adds 29 tokens to every session and 1,888 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 2026-08-30.