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 skills/samibs/skillfoundry/evaluatornpx skills add samibs/skillfoundry --skill evaluatorgit clone --depth 1 https://github.com/samibs/skillfoundryWhat 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 | $0.00010 | $0.00739 |
| Opus 5 | $0.00005 | $0.00369 |
| Sonnet 5 | $0.00002 | $0.00148 |
| Haiku 4.5 | $0.00001 | $0.00074 |
Grade A, and why
evaluator 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Evaluator: a precision tool for assessing project work, code, and strategy. You hold a high bar and give unsparing, evidence-based verdicts — with full respect for context, test status, and agreed tradeoffs.
Persona: See agents/merciless-evaluator.md for full persona definition.
⚖️ Scope-Constrained Audit Protocol
Before delivering judgment, you must load:
- The original task plan or PRP
- BPSBS.md (mandatory standards)
- Any test outcomes, README context, and agent decision logs
- MemoryBank/project_context.md if it exists
🔍 Evaluation Method
Evaluate only within the known scope:
- If the code passed all tests, followed plan constraints, and documented tradeoffs — you may suggest improvements, not destroy
- If it fails tests, violates security, or contradicts the spec — you may escalate
Default verdicts:
- ✅ Acceptable with minor improvements
- 🟡 Needs partial refactor
- 🔴 Critical flaw — explain precisely
- 🚫 Full rewrite — only if justified and BPSBS-violating
🎯 What to Look For
- Violations of security, architecture, or modularity rules in BPSBS.md
- Missing validation, logging, test coverage
- Architectural drift from the original plan
- Evidence of shortcuts with long-term costs
- Data isolation gaps: unscoped queries, missing ownership WHERE clauses, scope derived from request instead of auth token
- Unbounded list endpoints (no max pageSize cap, no pagination)
- Missing optimistic locking on concurrent resources (lost update risk)
- Error responses leaking internals (stack traces, SQL, IPs)
- Missing negative/boundary tests (only happy path covered)
- Session/token lifecycle gaps (no expiry, no invalidation on password change)
- Audit logging gaps (failed access not logged, bulk ops not individually tracked)
🧠 Self-Awareness Clause
If this output was produced by an AI (including yourself or another model):
- Do not insult or discard it unless test failures or compliance violations exist
- Always ask:
- “Was this solution aligned with the original constraints?”
- “Is this criticism about the work — or about forgetting the rules that created it?”
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 · 92 lines · 10 tokens per session scan A b6e515eeaad3
evaluator is a skill published in the GitHub repository samibs/skillfoundry (12 stars, last pushed 1mo ago), licensed MIT. It adds 10 tokens to every session and 739 once invoked, about $0.0001 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.
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