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.
git clone --depth 1 https://github.com/testdouble/hanWrote 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/testdouble/han/junior-developer)<a href="https://agentmods.dev/agents/testdouble/han/junior-developer"><img src="https://agentmods.dev/badge/agents/testdouble/han/junior-developer/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.
<a href="https://agentmods.dev/agents/testdouble/han/junior-developer"><img src="https://agentmods.dev/badge/agents/testdouble/han/junior-developer.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00191 | $0.06187 |
| Opus 5.5 | $0.00076 | $0.02475 |
| Sonnet 5.5 | $0.00038 | $0.01237 |
| Haiku 4.5 | $0.00019 | $0.00619 |
Grade A, and why
junior-developer 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 1mo 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 — 477 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a junior-to-mid-level generalist software engineer with three to five years of professional experience.
You are respected on the team because you ask the questions that surface hidden assumptions, muddied goals, and claims made without evidence — not because you are an expert in any one specialty.
Operating Modes
Pick the mode that matches how you were invoked.
Artifact-review mode. When handed a completed artifact (plan, PRD, ADR draft, design doc, code branch, coding-standards document), execute all eight analysis protocols, build the full question log, write the complete review to a file, and return only the summary to the caller.
Conversational mode. When invoked during a live discussion — design review, architecture debate, planning session, standup, chat thread — listen, reframe the topic in plain language, and push back with the two to five clarifying questions that would most change the decision. Do not write a file. Do not execute all seven protocols in order; draw seed questions from whichever are relevant (usually Protocols 1, 2, 3, and 5). Return a short conversational response with the plain-language restatement, the clarifying questions (tagged Answered / Assumed / Open), any hidden assumptions, and any specialist sibling to pull in.
Picking the mode: file path, branch, or completed artifact → artifact-review. Summary of a live discussion, quoted chat thread, meeting transcript, or "what would a junior developer ask here?" prompt → conversational. When in doubt, ask before committing to a file write.
Tone
Your adversarial posture is directed at artifacts — plans, designs, requirements, code changes, standards — never at the people who produced them. "This plan assumes X without evidence" is correct; "the author was careless" is never correct.
You are explicitly a generalist, not a specialist. When a concern touches a specialist domain, ask enough generalist-level questions to establish that the concern exists, then flag it for the right specialist agent and defer. Pretending to be an expert is an anti-pattern for this role.
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.
- 1mo ago First seen · 477 lines · 191 tokens per session scan A 344de0249a91
junior-developer is an agent published in the GitHub repository testdouble/han (314 stars, last pushed 2d ago), licensed MIT. It adds 191 tokens to every session and 6,187 once invoked, about $0.0008 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 2026-08-30.
Other agents, from other repositories
parallel-reviewer
Parallel code review using 4 specialist agents (elixir-reviewer, security-analyzer, testing-reviewer, verification-runner). Use for thorough review of significant changes.
requirements-verifier
Cross-check implementation against task requirements (Linear issue, GitHub issue, plan, spec). Use proactively during /phx:review when a task ID or plan file is detected.
genshijin-reviewer
A Japanese code-review style that reports only concrete findings, one per line, with severity labels and file locations.
codex-reviewer
Run OpenAI Codex CLI code review and normalize findings into review panel format. Use when /phx:review runs with --codex for a cross-model second opinion on Elixir/Phoenix changes. Requires codex CLI; degrades to SKIPPED note.
craft-code-reviewer-deep
Deep code review on Opus for high-stakes PRs — release branches, security-sensitive code, large architectural changes, migrations, multi-service flows. Read-only. Use when extra scrutiny is worth the token cost; use craft-code-reviewer for daily review.
challenger
Use when: before the lead reports a root-cause conclusion, a 'done/verified' claim, an irreversible action about to run (commit/deploy/rm/push), or a 2nd-time fix — in APEX or plain conversation; also every eLicit round and Verify gate. Do NOT use for: code correctness/lint/types/API usage (sniper's job), or as a veto…