You keep typing the way you always do. It reads, asks around, remembers, and writes down what helped.

A second opinion before the first edit · repo memory opened only when it pays · a record of what helped, for future evolution

You know the codebase, you know your personal preferences, now let your agents know as well.

Every request, while MiHa is on:

1. Infer the task tag           → update · debug · refactor · query · check · exec · pr · init · loop
2. Gate the evidence            → one external fact with a known source is fetched directly; advisors
                                  spawn only on a signal the route hook injects: research or alternatives
                                  words in the prompt, or shell errors that point at version drift
                                  (a docs lookup, then the online-researcher, then the devil's advocate)
3. Read repo memory on need     → preference.md is the one standing read; `begin` prints the matching
                                  routes (symptom → entry files → tests → verify command); the rest only when it pays
4. Do the work the native way   → your platform's own flow, permissions, and tools
5. Finish the run's record      → `mh.sh begin` opened it, `mh.sh end` fills it from flags, writes memory, and seals it
6. Consolidate on request       → wiki folds trajectories into harness_effect.md

The advisors are waited on at one boundary for at most the advisory budget (5 minutes by default), and only the next action that depends on their answer waits; independent work proceeds. Source-dependent actions and claims require verified evidence; unverified parts remain unresolved on timeout. Their findings are dispositioned by the main agent: adopt, partly adopt, keep for later, or reject. Those decisions go in the trajectory, not in a checklist you have to click through.

Lazy about ceremony, never about evidence: the advisors read the real code, the researcher cites every source, and the verifier never edits.

Pick one host. Each takes one to two minutes.

/plugin marketplace add HangYu8123/mini-harness

/plugin install mini-harness@mini-harness

/mini-harness:mini-harness on

The third command also creates .harness/ in the repo (protocol copy, repo_info/, exec_traj/, state/). The plugin's own hook and agents cover the rest.

To try it without installing: claude --plugin-dir /path/to/mini-harness.

git clone https://github.com/HangYu8123/mini-harness.git
bash mini-harness/install.sh /path/to/your-repo

The installer writes .harness/, the skills into .agents/skills/ and .claude/skills/, the workers into .claude/agents/ and .codex/agents/, a six-line block in AGENTS.md, a CLAUDE.md importing it, and a routing hook that stays silent until on. Every file it writes is listed in .harness/installed.tsv. A same-named file it did not install, or one you edited, is kept and reported (--force overwrites). Run it again to update; --uninstall removes what it owns and keeps the memory.

Add --guard for a hook that hard-blocks sudo, git push, git commit, and tree-wide deletes even when you ask for them. It is opt-in; without it your permission prompts decide.

Codex: hooks are skipped until trusted. Run /hooks once in Codex and trust the two mini-harness entries.

codex plugin marketplace add HangYu8123/mini-harness

Install from /plugins, then:

bash mini-harness/install.sh /path/to/your-repo --no-hooks

Codex plugins carry no custom agents, so the installer adds .codex/agents/ (plus the standalone skills and .harness/; --no-hooks only avoids a second routing hook next to the plugin's). In Codex run /hooks, trust the plugin's route hook, then $mini-harness on.

Open a new session and run /mini-harness doctor (Codex: $mini-harness doctor). It should print the resolved root and ok lines, never "unknown skill".

That was it. The cat did not wake up.

1. /mini-harness on (Codex: $mini-harness on; plugin: /mini-harness:mini-harness on).
2. Once per repo: /mini-harness init. Builds the memory under .harness/repo_info/ using loaded worker settings. Only an explicit setting change requires a restart; the resumed init restores its saved settings when complete.
3. Ask for anything the way you always do.
4. /mini-harness off when you want the plain platform back.

No configuration or advisor approval is needed for an ordinary request. The task type is inferred; override it with a task: debug line if you want. Advisors never spawn on the agent's own judgment, only on a signal the route hook injects: research words in the prompt (the latest version, SOTA, papers, which library) call the online researcher, alternatives words (trade-offs, a design choice) the diversifier, and shell errors that point at version drift escalate within a request from a direct docs lookup to the researcher to the devil's advocate. No signal, no advisor; a single fact with a known source is still fetched directly. on / off dials force either way. Recording is automatic. The final answer focuses on the result and its verification, with no routine status footer.

Codex: $mini-harness …. Plugin install on Claude Code: /mini-harness:mini-harness …. Direct skills: /mh-init, /mh-loop, /mh-wiki, /mh-eval, /i-have-adhd.

When a job is mostly reading — a big crawl, hundreds of files — you may want the subagents on a cheap model at a high effort, or many of them at a low one, without paying your main model's price for each.

$mini-harness subagents on codex-model=gpt-5.6-luna effort=max
$mini-harness subagents on codex-model=gpt-5.6-luna effort=low
$mini-harness subagents off

Claude Code uses /mini-harness subagents …, for example on claude-model=haiku. Add effort=<level> for repo-installed workers when that model supports it. subagents without arguments shows the current selection; researcher=<level> selects a separate effort for the online researcher. Request any fan-out in your task; changing effort never adds agents by itself.

It is off by default and separate from /mini-harness on. While on, it changes only subagent model and effort: whether, when, and how many subagents run stays the platform's call, and your main session is untouched.

Explicit request settings take precedence where native controls allow; the toggle never swaps roles or changes context to force an override. Requested effort levels depend on model support. Definition changes, including restoration with off, require a new session; already running agents are unchanged. Shared plugin definitions and user-authored agents are left alone. Re-run install.sh for older standalone installs to wire the Agent hook (/mini-harness doctor checks it).

Two files in the pack root are a small GUI for writing a MiHa request without typing the dials by hand.

• harness_gui.html is the page: nine task tabs plus a Subagents tab, dials as buttons, one text box per field, and a live preview. Subagents builds Turn on, Turn off, or Check status commands with independent model/effort selections; it defaults to off and never applies settings itself. The page is self-contained; double-click it to use it offline. It never writes to disk.
• harness_gui.py is the launcher: python3 harness_gui.py serves the page locally, reloads templates live from request_template/, and adds a Browse button that inserts real repo-relative paths.

Pick the platform (it sets the invocation token), pick the task tab, flip the dials, fill the fields, copy, paste. It protects you from a misspelled dial, a dial that does not exist for that task, a wrong token for the platform, and out-of-date init defaults.

.harness/repo_info/ is read on need. Its README.md says when each file pays.

.harness/exec_traj/ holds one file per run (<timestamp>_<task>_<id>.md, never overwritten): what ran, what the advisors contributed, what changed, and the helped / hurt lines the wiki is built from. begin and end are the only bookkeeping calls; a line the run cannot supply stays unknown, and the usage figure is settled later beside the record (state/usage/), never inside the sealed file.

harness/          harness.md (the protocol core, ≈1.2k tokens) · advisory.md · tasks.md · exec_traj.md · philosophy.md · loop_control.md · stay_active.md · repo_map.md · reinitialize.md · worker_models.md
skills/           mini-harness (entry + mh.sh + mh_usage.py) · mh-init · mh-loop · mh-wiki · mh-eval (A/B benchmark, mh_eval.py) · i-have-adhd (vendored, MIT) · breakdown-pr · code-simplification · code-review-and-quality
agent_sources/    nine workers → agents/ (Claude Code, plugin) · .codex/agents/ via sync_agents.py
hooks/            route.sh (activation routing) · guard.sh (optional) · plugin and standalone hook configs
harness_gui.*     the request builder, fed by request_template/*.md

The nine workers: online-researcher, diversifier, devils-advocate (the advisors) · focus-analyst, broad-analyst, free-analyst (analysis) · implementer, executor, verifier (doing and checking).

agent_sources/*.agent.md is the single source for every worker. After editing one:

python3 sync_agents.py          # regenerates agents/ and .codex/agents/; never hand-edit those
python3 sync_gui_templates.py   # after editing request_template/*.md

The three advisors carry omitClaudeMd: true: on Claude Code (v2.1.271+) they start without the repo's CLAUDE.md / AGENTS.md, since their prompt and the generated working rules carry what they need. Codex has no such field.

Keep files short: harness.md is the core at about 1.2k tokens (every byte is re-sent on every call), each SKILL.md at most about 2.5k, satellites at most about 1.5k. Every rule traces to a real failure. Delete rules that stop earning their tokens.

Release criterion — the 10% rule. A change to the layer ships only when, on a frozen paired workload (same tasks, trees, models, effort, tools, and cache conditions; policies and worker definitions snapshotted outside the tree being edited), the ON arm's total tokens are at most 1.10 × the OFF arm's — counting main-thread replay, descendants, retries, and the consolidation sessions the hook launches — with task quality held by held-out checks. Save each arm with mh.sh usage --json --all > on.json / off.json (add --rates <file> to price them per model and cache category) and run mh.sh usage --compare on.json off.json: it prints the pooled ratio, the per-pair ratios, money separately from tokens, and PASS or FAIL (exit 1). /mini-harness eval (skills/mh-eval) runs the whole paired workload for you: two disposable worktrees (harness on · off), the same questions in each as headless sessions, usage --compare, and a report to grade the pairs in. The last recorded experiment (2026-09-22, analysis/sandbox_eval/) measured +47% input; the target has not been met yet, and nothing here claims it has.

Design sources: arXiv 2609.00006 (eleven-system harness study), 2603.25723 (natural-language harnesses), 2604.25850, 2606.20631, 2608.27454 (WikiSkill), LangChain's isolated-verifier rule (Sep 2026), and the conventions of obra/superpowers, mattpocock/skills, addyosmani/agent-skills, garrytan/gstack, ayghri/i-have-adhd.

Does it replace my platform's workflow? No. The native flow runs as usual. MiHa adds the tag, the advisors, the memory, and the record around it, and gets out of the way when you say off.

Will it slow me down? The advisors run in the background and only the next action that depends on their answer waits, for at most the advisory budget. A request whose prompt carries no signal words and whose commands hit no version-drift errors gets no advisors at all. mh.sh usage reports what a session or a run cost, and mh.sh usage --compare checks the 10% release criterion — which the recorded experiment does not yet meet.

Will it commit or push? Only when you ask. It never uses sudo, and by default never lists Claude, Codex, or itself as author, co-author, contributor, or trailer in commits, PRs, or file headers. Your permission prompts stay the authority; --guard adds a hard block if you want one.

Why a sleeping cat? 摸鱼. The cat naps while the advisors work.