challenge-resolve

challenge-resolve is a skill for Claude Code, Codex from Borda/AI-Rig. It costs 47 tokens per session (1,970 once invoked), scanned A, original, Apache-2.0.

A bounded workflow for reviewing a code change, fixing issues found in that review, and repeating the review when needed. It requires a goal, file scope, expected behaviour, and a condition for completion.

In plain words
What is it for?
It is for adversarial review-and-fix loops on a specified diff or set of files. It can apply feasible in-scope fixes and finish with an independent review and normal checks.
Why use it?
It prevents an open-ended review-and-fix process by limiting the scope, recording evidence, and defining when to stop or recover.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is Before asking, read [User Questions](../../shared/codex-user-questions.md)..

Good fit It is for adversarial review-and-fix loops on a specified diff or set of files. It can apply feasible in-scope fixes and finish with an independent review and normal checks.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/Borda/AI-Rig
agentmods
npx agentmods add skills/borda/ai-rig/challenge-resolve

Made for: Claude Code, 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.

agentmods badge for challenge-resolve

README.md
[![agentmods](https://agentmods.dev/badge/skills/borda/ai-rig/challenge-resolve/github.svg)](https://agentmods.dev/skills/borda/ai-rig/challenge-resolve)
Your own site
<a href="https://agentmods.dev/skills/borda/ai-rig/challenge-resolve"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/challenge-resolve/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.

agentmods 80×15 button for challenge-resolve

Your own site · 80×15
<a href="https://agentmods.dev/skills/borda/ai-rig/challenge-resolve"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/challenge-resolve.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,970 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 $0.00047 $0.01970
Opus 5.5 $0.00019 $0.00788
Sonnet 5 $0.00009 $0.00394
Haiku 4.5 $0.00005 $0.00197

Measured 2d ago against content hash 2a2efa72820b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-26, from the pricing page.

Security

Grade A, and why

challenge-resolve 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.

The scan reads SKILL.md. This mod also ships 1 executable file (validate_evidence.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/codex-rig/skills/challenge-resolve/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Before asking, read User Questions.

Challenge and Resolve

Read, apply ../../shared/adversarial-loop.md before dispatch or edits. That shared procedure owns the algorithm; this entrypoint owns Codex artifacts, the closing gate. Read evidence-contract.md before source capture or reviewer dispatch. Also read ../../shared/native-skill-contract.md and ../../shared/specialist-orchestration.md for authority, recurrence, reviewer admission, evidence limits.

Input Schema

{
  "goal": "required review-and-fix objective",
  "scope_files": ["bounded files or diff scope"],
  "specification": "required behavior or acceptance criteria",
  "symptom": "reported failure, or explicit preventive review",
  "caller_run": "optional existing workflow run to resume",
  "done_when": "independent final review is clean and normal checks pass"
}

Use default max 3 review rounds, including initial W_0. In-scope feasible fixes are authorized by a review-and-fix request; a structural finding does not authorize scope expansion, public API changes, commits, installs, network access or publication. A caller's stricter scope or admission still applies.

Workflow

01: Establish scope and evidence ownership

Read ../../shared/helper-cli-contract.md; create a run with create_run.py --skill challenge-resolve. Record caller_run when supplied, without overwriting its artifacts. Retain baseline source and acceptance evidence. Write loop-report.md with Scope, Rounds, Findings, Recovery, and Verification sections. Identify implementation author and allowed reviewer route before dispatch.

02: Run the shared bounded procedure

Follow the shared five-step procedure: challenge and collect findings; report the old/new table once after each validated round; resolve every feasible in-scope finding; escalate unresolved security, critical or high; repeat until clean, three rounds, plateau or a non-converging score. Retain loop-ledger.json, loop-actions.json, round-<index>.diff, current snapshot current.diff and each independent report. Read adversarial_loop.py --help, validate the ledger after each round, and invoke adversarial_loop.py --ledger <run-directory>/loop-ledger.json --progress only after a newly completed challenge, before the next fix, review or stop. Show its full cumulative stderr table with Iteration | Critical | High | Medium | Low | Nits | Weighted score and literal old + new cells. Never show a placeholder progress table before a validated round or repeat the table in unrelated status updates. Keep the final canonical Results table unchanged. Structural or repeated findings alone do not stop an authorized feasible fix; scope, authority, recurrence, plateau, missing independence, stale evidence and exhausted rounds retain their shared stop rules. A fixed-pending-verification finding remains open. After resolution/escalation, bind every open finding to an action and run adversarial_loop.py --ledger <run-directory>/loop-ledger.json --actions <run-directory>/loop-actions.json before another challenge or final handoff. The helper validates recorded actions, not their truth; the parent must inspect feasibility and fix evidence.

Read the full file on GitHub · 79 lines

Files

What ships with it

3 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. 2d ago First seen · 79 lines · 47 tokens per session scan A 2a2efa72820b

Subscribe to this mod's changes

challenge-resolve is a skill published in the GitHub repository Borda/AI-Rig (28 stars, last pushed 3d ago), licensed Apache-2.0. It adds 47 tokens to every session and 1,970 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-24.

Related

Other skills, from other repositories

morpheus

Second opinion and final verdict for engineering decisions. Challenges a plan, design, PR, claim, fix, or bug theory with cited evidence, steelmans the user's position first, asks when an assumption would flip the verdict, labels how each claim is known, and always lands on a verdict or a recommended option with…

CassioRoos/godfly-skills · 151 tokens

sentry-brief

Turn a raw alert payload into a one-screen incident brief: blast radius, suspected cause, the three checks that discriminate between causes, and the containment action. Use when paged, when triaging an alert, or when handing an incident to the next responder.

CassioRoos/godfly-skills · 57 tokens

transcript-grep

Search a Claude Code session transcript for a string or regex pattern and show every matching message with surrounding context. Reads /api/sessions/:id/transcript and resolves sessions via /api/sessions?limit= from the Agent Monitor dashboard. Use when hunting for a specific message, prompt, tool call, or error inside…

hoangsonww/Claude-Code-Agent-Monitor · 73 tokens

anomaly-alert

Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error…

hoangsonww/Claude-Code-Agent-Monitor · 86 tokens

audit

Project health audit and health check — architecture, performance, tests, dependencies, code quality. Use when assessing overall project health, before releases, or after refactors.

oliver-kriska/claude-elixir-phoenix · 35 tokens

regression-watch

Detect quality and efficiency regressions over time using Agent Monitor data — rising error rate (APIError events), falling cache hit rate, growing compaction frequency, and climbing cost-per-session. Splits history into an earlier baseline window and a recent window and reports which metrics are getting worse, by how…

hoangsonww/Claude-Code-Agent-Monitor · 82 tokens