FlowGuard: Skill for Codex

.agents/skills/flowguard-model-miss-review/SKILL.md

flowguard-model-miss-review is a skill for Codex from liuyingxuvka/FlowGuard. It costs 26 tokens per session (637 once invoked), scanned A, original, MIT.

A review process for finding the underlying planning or test gap after a previously successful FlowGuard check fails in real use. It connects the failure to the affected commitment, code, tests, and claim.

In plain words
What is it for?
Use it after a runtime, test, replay, log, manual, or interface failure to classify the missed behavior and document the needed generalized repair.
Why use it?
It prevents a narrow point fix from hiding a broader missed behavior. The process requires concrete failure evidence before recommending closure.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is liuyingxuvka/FlowGuard's own configuration. It tells Codex how to work on FlowGuard itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything FlowGuard configures →

Reuse

Borrowing it

Nothing to install: this file belongs to liuyingxuvka/FlowGuard. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/liuyingxuvka/FlowGuard/main/.agents/skills/flowguard-model-miss-review/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/liuyingxuvka/FlowGuard

Made for: Codex.

Wrote 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.

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README.md
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Your own site
<a href="https://agentmods.dev/skills/liuyingxuvka/flowguard/flowguard-model-miss-review"><img src="https://agentmods.dev/badge/skills/liuyingxuvka/flowguard/flowguard-model-miss-review/github.svg" alt="Measured on agentmods" height="20"></a>

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Your own site · 80×15
<a href="https://agentmods.dev/skills/liuyingxuvka/flowguard/flowguard-model-miss-review"><img src="https://agentmods.dev/badge/skills/liuyingxuvka/flowguard/flowguard-model-miss-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 637 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00026 $0.00637
Opus 5 $0.00013 $0.00318
Sonnet 5 $0.00005 $0.00127
Haiku 4.5 $0.00003 $0.00064

Measured 11d ago against content hash dd9761c11455, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

flowguard-model-miss-review 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 11d 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.

.agents/skills/flowguard-model-miss-review/SKILL.md · 43 lines

How it starts

The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.

FlowGuard Model Miss Review

Purpose

Apply root-cause backpropagation from a post-green failure into its commitment, blueprint gap, finite cases, owner code/tests, and claim.

Entrypoint Scope

This standalone FlowGuard satellite skill owns grounded model_miss_review classification and closure, not feature invention.

Local Material Routing

After admission, read references/model_miss_protocol.md for the full protocol.

Entrypoint Acceptance Map

Accept concrete failure evidence and prior claim state; block point-fix-only or stale closure.

Use When

  • Use after a FlowGuard-green runtime, test, replay, log, manual, or UI failure, including boundary_missing.

Do Not Use When

  • Do not invent a commitment or proceed without concrete failure evidence; return unclear modeling to flowguard.

Required Workflow

  1. Run Existing Model Preflight; bind one commitment, primary owner, complete current-effective-intent owner binding, blueprint gap, error signature, and miss type. If nothing covers the promise, record one coverage gap.
  2. Backpropagate only the supported cause. A requested diagnostic is a read-only deletion-minimal conflict plus positive witness and preserves the owner decision.
  3. Declare finite relations from current DNA/BCL/topology identities and pass exact relation/gap ids to ContractExhaustionMesh; no unbounded sibling search or second relation authority.
  4. Materialize each contract-exhaustion same-class case, combination, or receipt with an oracle; emit one task-bound ModelMaturation contribution.
  5. Bind cases to the owner code contract and tests. Rerun alignment, affected topology/parent replay, freshness, and maturation risk; close or scope the class.

Hard Gates

  • Model-purpose gate: freeze task-specific failure(s) and claim boundary; bind the candidate to native good/bad-per-failure/oracle/current evidence. Reusable types are not fixed-purpose: no mode/fallback; only FlowGuard-declared checks may support completion claims. Require the real FlowGuard check engine and AGENTS.md managed record; forbid a fake mini-framework.
  • A later green command or point regression cannot close the class; require target-aware replay and owner-code binding.
  • Current intent comes only from the accepted complete CurrentEffectiveIntentView; never infer repaired DNA from delta, history, root intent, or code path.
  • Unknown old-path disposition, unresolved canonical case, missing owner-code/test binding, stale parent/topology replay, or open ModelMaturation gap blocks broad confidence.
  • Shared symptom text never merges behavior planes. Diagnostics need necessity and positive witnesses; say deletion-/subset-minimal, never global-minimum or unique.

Read the full file on GitHub · 43 lines

Files

What ships with it

5 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.

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. 11d ago First seen · 43 lines · 26 tokens per session scan A dd9761c11455

Subscribe to this mod's changes

flowguard-model-miss-review is a skill published in the GitHub repository liuyingxuvka/FlowGuard (2 stars, last pushed 16d ago), licensed MIT. It adds 26 tokens to every session and 637 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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