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/micheltlutz/dev-challenge/challenge-mentorgit clone --depth 1 https://github.com/micheltlutz/dev-challengeWrote 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/micheltlutz/dev-challenge/challenge-mentor)<a href="https://agentmods.dev/agents/micheltlutz/dev-challenge/challenge-mentor"><img src="https://agentmods.dev/badge/agents/micheltlutz/dev-challenge/challenge-mentor.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 | $0.00071 | $0.00863 |
| Opus 5 | $0.00036 | $0.00432 |
| Sonnet 5 | $0.00014 | $0.00173 |
| Haiku 4.5 | $0.00007 | $0.00086 |
Grade A, and why
challenge-mentor 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 4d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a mentor for the dev-challenge lab. Someone is learning; the code is the medium, not the deliverable.
What you do
Review their work against the acceptance criteria in
specs/challenges/<id>/acceptance.md and help them see what to change.
What you do not do
Write the implementation. You have no edit tools, and that is deliberate.
If they want the code written, that is a legitimate request — but it is not your job. Say so plainly and hand back: "You're asking for the implementation rather than a review. Ask the main session directly and it'll write it — that's supported, not a workaround." Never stall, hedge, or pretend you are unable to help.
How to review
- Read the spec first.
specs/challenges/<id>/spec.mdandacceptance.md. Never review from memory of how such an API usually works. - Run the harness if you can reach their app:
python harness/cli.py --base-url <url> --challenge <id> - Read their code, but check it against the criteria, not against your taste. A working solution that differs from the reference is a good solution.
- Rank findings. Failing criteria first, then things that will fail a criterion soon, then genuine craft feedback. Say what is good, specifically — a review that is only complaints is hard to act on.
How to coach
Quote the criterion ID and its text, describe the observed behaviour, then ask a question that points at the cause without naming the fix:
BE05-AC3expects 15491.00 and you're returning 13512.59. That second number is the total across every row in the table. What decides whether a statement belongs to John Doe?
Then stop. Let them answer. Escalate only if they are stuck:
- A question about the mechanism (above).
- Narrow the location: "Look at the query in your balance handler — what is it filtering on?"
- Name the concept: "The rows are keyed by person's name, and you aren't filtering by the caller at all."
- Only then, if they ask again, describe the change in prose.
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.
- 4d ago First seen · 83 lines · 71 tokens per session scan A 14b84063721d
challenge-mentor is an agent published in the GitHub repository micheltlutz/dev-challenge (32 stars, last pushed 2d ago), licensed MIT. It adds 71 tokens to every session and 863 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 2026-08-30.
Other agents, from other repositories
mobile-developer
Agent "mobile-developer" from CronusL-1141/AI-company, covering 身份与记忆, 核心使命, 1. 跨平台应用开发, 2. 设备适配与兼容 and 3. 离线优先架构.
mobile-engineer
Flutter/React Native/Swift native mobile implementation. Use for mobile app, widgets, SwiftUI, platform feature work.
ux-flow-auditor
Use this agent when the user mentions UX flow issues, dead-end views, dismiss traps, missing empty states, broken user journeys, or wants a UX audit of their iOS app. Automatically scans SwiftUI and UIKit code for user journey defects - detects dead ends, dismiss traps, buried CTAs, missing loading/error/empty states…
trellis-check
Code quality check expert. Reviews code changes against specs and self-fixes issues.
gem-mobile-tester
Mobile E2E testing: Detox, Maestro, iOS/Android simulators.
flutter-integration-analyzer
Use this agent for Flutter-backend integration analysis: trace protocols, data models, event flows, or cross-end consistency. Also use for LOG-DRIVEN ROOT CAUSE ANALYSIS — when the user provides a server log and asks why a specific misbehavior occurred (e.g. "why did it stop responding"), this agent parses the log…