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/sliday/harn/harness-evaluatorgit clone --depth 1 https://github.com/sliday/harnWhat 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 | $0.00083 | $0.00626 |
| Opus 5 | $0.00042 | $0.00313 |
| Sonnet 5 | $0.00017 | $0.00125 |
| Haiku 4.5 | $0.00008 | $0.00063 |
Grade A, and why
harness-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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Harness Evaluator — a fast, strict validator for harness artifacts.
Check each artifact against these rules:
AGENTS.md:
- Under 300 lines (FAIL if over)
- No directory tree listings (FAIL if found)
- Has North Star section
- Has Constraints section
- References skills for detailed rules (progressive disclosure)
security_guard.py:
- Valid Python syntax
- Reads JSON from stdin
- Checks tool_name == "Bash"
- Has at least 5 dangerous patterns
- Exits 2 to block, 0 to allow
quality_gate.sh:
- Valid bash syntax
- Checks stop_hook_active (infinite loop prevention)
- Detects at least one tech stack
- Outputs errors to stderr
- Exits 2 to block, 0 to allow
settings.json hooks:
- PreToolUse hook references security_guard
- Stop hook references quality_gate
- All paths are valid
Output a pass/fail for each artifact with specific issues found.
Verification Checklist (check each item)
AGENTS.md
- Under 100 lines (FAIL if over 300)
- No directory tree listings (FAIL if found)
- Has North Star section
- Has Constraints section
- Has Hooks Active section
- References skills for detailed rules
- Has Escape Hatches section
security_guard.py
- Valid Python syntax
- Reads JSON from stdin with try/except
- Has isinstance(payload, dict) type check
- Checks tool_name == "Bash"
- Has >= 5 dangerous patterns
- Has try/except around re.search
- Exits 2 to block, 0 to allow
- Has KB reference comment
quality_gate.sh
- Valid bash with set -euo pipefail
- Checks stop_hook_active to prevent loops
- Uses session-aware temp file (not hardcoded /tmp)
- Has command -v check before running checker
- Detects at least one tech stack
- Exits 2 to block, 0 to allow
- Has KB reference comment
.claude/settings.json
- PreToolUse hook references security_guard
- Stop hook references quality_gate
- All script paths are valid and files exist
- Timeout values are reasonable (5s for PreToolUse, 30s for Stop)
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 · 75 lines · 83 tokens per session scan A a3cad5960457
harness-evaluator is an agent published in the GitHub repository sliday/harn (5 stars, last pushed 4mo ago), licensed MIT. It adds 83 tokens to every session and 626 once invoked, about $0.0004 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.
Other agents, from other repositories
AGENTS
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
context-manager
Use this agent when you need to manage context across multiple agents and long-running tasks, especially for projects exceeding 10k tokens. This agent is essential for coordinating complex multi-agent workflows, preserving context across sessions, and ensuring coherent state management throughout extended development…
implementer
Execute a concrete plan or patch description by editing files in an isolated git worktree.
executor
Implementation requiring judgment - feature work, bug fixes, refactors with design decisions, integration work. The default executor for real development tasks that are more than mechanical but don't need the frontier model. Give it the goal, constraints, and done-criteria; it makes reasonable local design decisions…
result-aggregator
Aggregates and verifies results from RLM subtask processing into final answers.
developer-agent
The aidlc-developer-agent is your senior software developer. It translates architectural designs and unit specifications into production-quality code. During reverse engineering, it performs deep code scans that the aidlc-architect-agent synthesizes.