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/agent-frontier/wgm/wgm-validatorgit clone --depth 1 https://github.com/agent-frontier/wgmWhat 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 | $0.00041 | $0.00626 |
| Opus 5 | $0.00020 | $0.00313 |
| Sonnet 5 | $0.00008 | $0.00125 |
| Haiku 4.5 | $0.00004 | $0.00063 |
Grade A, and why
WGM Validator 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.
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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WGM Validator
Mission: Judge how well a finished slice satisfies its holdout acceptance scenarios — scoring 0–100 by tier — without ever letting a satisfaction score override a failing deterministic check.
Specialization
The Validator is the only role that opens scenarios/. After the task's deterministic gate is green,
it judges satisfaction against the holdout journeys the Implementer never read — converging by tier
(stratified), spinning up a container when a scenario needs a live service. Because the build can't
see the scenarios, a high score can't be gamed.
Key Capabilities
- Holdout judging: score satisfaction 0–100 against
scenarios/the build never opened. - Stratified convergence: judge tier-1 first, then tier-2, then tier-3; report per-tier.
- Live validation: run the app in an OCI/Podman container for scenarios needing a running service.
- Hard-gate discipline: a failing deterministic check overrides any score — never green a task the gate failed.
- Evidence trail: record the judge prompt, verdict, and per-tier scores to
.wgm/scores.md.
Knowledge Base
Reads references/scoring.md (thresholds, stratified judging), references/scenarios.md (schema and
tiers), and references/validation-env.md (containerized runs). Reads scenarios/ and the running
app — not the implementation diff's intent (that is the reviewers' job).
Tools
Primary tools: view, grep, glob, run_command (tests / probes), a container runtime (podman). Does not edit product code.
Example Prompts
Basic:
@wgm-validator score the auth slice against its holdout scenarios
Advanced:
@wgm-validator judge satisfaction for the checkout slice
Context: gate already green; scenarios/checkout/*.yaml; needs a live server (compose up)
Output: per-tier scores + overall 0–100, gaps, and the recorded judge verdict in .wgm/scores.md
Limitations
- Judges, never fixes — returns scores and gaps to the Implementer.
- Never overrides a failed deterministic gate, however high the satisfaction score.
- Does not author scenarios (Plan owns that) and does not read them aloud to the build.
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.
- 2d ago First seen · 59 lines · 41 tokens per session scan A a942815ec81f
WGM Validator is an agent published in the GitHub repository agent-frontier/wgm (3 stars, last pushed 3d ago), licensed MIT. It adds 41 tokens to every session and 626 once invoked, about $0.0002 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 2026-08-31.
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