Borrowing it
Nothing to install: this file belongs to priyanshuchawda/tracepilot-gemini-cli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/priyanshuchawda/tracepilot-gemini-cli/main/.gemini/skills/behavioral-evals/SKILL.mdgit clone --depth 1 https://github.com/priyanshuchawda/tracepilot-gemini-cliWrote 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/skills/priyanshuchawda/tracepilot-gemini-cli/behavioral-evals)<a href="https://agentmods.dev/skills/priyanshuchawda/tracepilot-gemini-cli/behavioral-evals"><img src="https://agentmods.dev/badge/skills/priyanshuchawda/tracepilot-gemini-cli/behavioral-evals/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/skills/priyanshuchawda/tracepilot-gemini-cli/behavioral-evals"><img src="https://agentmods.dev/badge/skills/priyanshuchawda/tracepilot-gemini-cli/behavioral-evals.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 | $0.00039 | $0.00616 |
| Opus 5 | $0.00019 | $0.00308 |
| Sonnet 5 | $0.00008 | $0.00123 |
| Haiku 4.5 | $0.00004 | $0.00062 |
Grade A, and why
behavioral-evals 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 9d 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.
This is a copy
100% identical to behavioral-evals — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavioral Evals
Overview
Behavioral evaluations (evals) are tests that validate the agent's decision-making (e.g., tool choice) rather than pure functionality. They are critical for verifying prompt changes, debugging steerability, and preventing regressions.
[!NOTE] Single Source of Truth: For core concepts, policies, running tests, and general best practices, always refer to evals/README.md.
🔄 Workflow Decision Tree
- Does a prompt/tool change need validation?
- No -> Normal integration tests.
- Yes -> Continue below.
- Is it UI/Interaction heavy?
- Yes -> Use
appEvalTest(AppRig). See creating.md. - No -> Use
evalTest(TestRig). See creating.md.
- Yes -> Use
- Is it a new test?
- Yes -> Set policy to
USUALLY_PASSES. - No ->
ALWAYS_PASSES(locks in regression).
- Yes -> Set policy to
- Are you fixing a failure or promoting a test?
- Fixing -> See fixing.md.
- Promoting -> See promoting.md.
📋 Quick Checklist
1. Setup Workspace
Seed the workspace with necessary files using the files object to simulate a realistic scenario (e.g., NodeJS project with package.json).
- Details in creating.md
2. Write Assertions
Audit agent decisions using rig.setBreakpoint() (AppRig only) or index verification on rig.readToolLogs().
- Details in creating.md
3. Verify
Run single tests locally with Vitest. Confirm stability locally before relying on CI workflows.
- See evals/README.md for running commands.
📦 Bundled Resources
Detailed procedural guides:
- creating.md: Assertion strategies, Rig selection, Mock MCPs.
- fixing.md: Step-by-step automated investigation, architecture diagnosis guidelines.
- promoting.md: Candidate identification criteria and threshold guidelines.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 57 lines · 39 tokens per session scan A c1ab849bb3b1
behavioral-evals is a skill published in the GitHub repository priyanshuchawda/tracepilot-gemini-cli (1 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 616 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to behavioral-evals, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
superpowers
Always-on. The main development method: Plan → TDD → Implement → Verify → Report. Use for ANY non-trivial task. Do not write code without a plan and a test. Complex tasks (>3 files) → split into atomic tasks. Bug fix → Prove-It Pattern (reproduce with a test before the fix).
test-driven-development
Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
testing-discipline
Use when the user wants to: add/fix tests, understand what is covered, determine whether something is "done", reproduce a bug with a test, check limits/rate-limit/failures, or when tests are written against a real DB/network. Covers: isolation from the prod store, domain-first tests, test names as a spec, boundary…
agentic-evals
Design evaluation contracts and test plans for agentic systems. Create deterministic tests, trajectory evals, quality dimensions, gold-set criteria, and CI gates before or after implementation. Use when asked for tests first, an eval plan, success criteria, non-deterministic testing, LLM-as-judge setup, or…
fable-judge
Adversarial verification of finished work: re-runs the claimed verifications, diffs what changed, detects false "done" claims, delivers an evidence-based verdict (VERIFIED / VERIFIED WITH CAVEATS / REFUTED). Use after any agent or model claims work is complete — "/fable-judge", "judge this work", "verify what it did".…
verification-before-completion
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always.