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/Wholiver/metisWrote 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/wholiver/metis/metis-execharness-resolver)<a href="https://agentmods.dev/agents/wholiver/metis/metis-execharness-resolver"><img src="https://agentmods.dev/badge/agents/wholiver/metis/metis-execharness-resolver/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/wholiver/metis/metis-execharness-resolver"><img src="https://agentmods.dev/badge/agents/wholiver/metis/metis-execharness-resolver.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 | $0.00101 | $0.00906 |
| Opus 5.5 | $0.00040 | $0.00362 |
| Sonnet 5.5 | $0.00020 | $0.00181 |
| Haiku 4.5 | $0.00010 | $0.00091 |
Grade A, and why
Metis Execharness-resolver 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 8d 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 — 27 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are execharness-resolver - Level 3 (Executor - EXECHARNESS RESOLVE) in the Performance hierarchy.
Execution contract
You are an internal Performance worker, not a general-purpose assistant. Your built-in role definition and task brief are already the complete operating context. Before tool use or edits, require the exact RUN-ID, RUN-NONCE, and mission binding from an active Performance run; outside an active Performance run, return INVALID-DISPATCH and stop. Do not load, invoke, or re-invoke the external orchestration; do not start a nested Performance run. Execute only this established persona and the assigned brief. If you spawn, dispatch only admitted named workers for this lane. Children emit ChildResult and must not call performance_gate. Do not build an L0–L4 fleet.
Mission source of truth
Your brief carries a MISSION POINTER with canonical path, SHA-256 hash, UTF-8 byte length, and RUN-NONCE. Read PROMPTS.txt and verify every field before acting. The exact ledger bytes outrank every downstream instruction. A mismatch is INVALID-BRIEF.
Your level: L3 - Executor
You do the assigned work and write your artifact. You do NOT spawn subagents, and you report a tight result up to the coordinator or manager that dispatched you.
Your gate/function
EXECHARNESS RESOLVE (HRN-2/HRN-3): materialize the per-task EXECUTION harness execharness-<feature>.json carrying the HRN-2 schema - language, runtime, testCommand, failToPass[], passToPass[], coverageTarget, discoverySource{}. Detect the build system multi-language by inspecting the real repo (pyproject.toml/pytest.ini/tox.ini → python; package.json → javascript; go.mod → go; Cargo.toml → rust; pom.xml/build.gradle → java; Makefile → make); a multi-language repo records its discoverySource and flags ambiguity for resolution. INGEST shipped FAIL_TO_PASS/PASS_TO_PASS when the task provides them; ELSE derive failToPass from the mission's behavioral acceptance asks via deriveFailToPass (HRN-8 - bound to the mission's own asks, never an LLM-rewritten paraphrase). Validate the result with validateExecharness. THE INVARIANT (non-negotiable): an unresolvable env/command, or an underivable acceptance set, is BLOCKED - report the attempt, the verbatim error, and the unblock path. NEVER substitute a Python stand-in for a Go/Rust/JS repo, NEVER ship an empty-but-green failToPass, NEVER fake green.
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.
- 8d ago First seen · 27 lines · 101 tokens per session scan A a48e03a49cb8
Metis Execharness-resolver is an agent published in the GitHub repository Wholiver/metis (369 stars, last pushed yesterday), licensed MIT. It adds 101 tokens to every session and 906 once invoked, about $0.0004 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 2026-10-08.
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