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 skills add jleechanorg/agent-orchestrator-ts --skill evidence-standardsgit clone --depth 1 https://github.com/jleechanorg/agent-orchestrator-tsWrote 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/jleechanorg/agent-orchestrator-ts/evidence-standards)<a href="https://agentmods.dev/skills/jleechanorg/agent-orchestrator-ts/evidence-standards"><img src="https://agentmods.dev/badge/skills/jleechanorg/agent-orchestrator-ts/evidence-standards/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/jleechanorg/agent-orchestrator-ts/evidence-standards"><img src="https://agentmods.dev/badge/skills/jleechanorg/agent-orchestrator-ts/evidence-standards.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 | $0.00027 | $0.10857 |
| Opus 5.5 | $0.00011 | $0.04343 |
| Sonnet 5.5 | $0.00005 | $0.02171 |
| Haiku 4.5 | $0.00003 | $0.01086 |
Grade A, and why
evidence-standards scanned grade A with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s http://localhost:8005/health >> "$EVIDENCE_DIR/server_state.txt" Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.run(["git", "fetch", "origin", "main"], timeout=10, capture_output=True) How it starts
The opening of the file, as written. The whole thing — 1,240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evidence Standards for All Testing and Verification
Core Principle
Evidence must prove what you claim. Mock data cannot prove production behavior.
Evidence Class System
Evidence requirements vary by project type. Choose the class that matches your project:
| Class | Examples | Required Evidence |
|---|---|---|
| Terminal/Backend | APIs, services, CLIs, scripts | run.json, metadata.json, evidence.md (git provenance + test output sufficient) |
| Integration | DB-backed services, external API clients | Terminal class + request_responses.jsonl + server runtime provenance |
| LLM/API | LLM integrations, model fine-tuning, API pipelines | Integration class + llm_request_responses.jsonl |
| UI/Browser | Web apps, rendered interfaces, user flows | Terminal class + UI/browser video evidence |
For mixed-class projects, apply all applicable requirements. If your project has no browser UI, skip the browser video requirements. If your project has no LLM layer, skip the LLM request/response capture.
Evidence is NOT one-size-fits-all. A backend bug fix with python -m pytest output and git SHA is valid evidence. Do not generate video evidence for terminal-only work unless the work specifically requires it.
Minimum Viable Evidence Checklist
Every test MUST capture these at minimum (copy-paste into test setup):
def capture_provenance():
"""REQUIRED: Capture all evidence standards."""
provenance = {}
# === GIT PROVENANCE (MANDATORY) ===
# For GitHub/GitLab with remotes: fetch first to ensure refs are current
subprocess.run(["git", "fetch", "origin", "main"], timeout=10, capture_output=True)
provenance["git_head"] = subprocess.check_output(
["git", "rev-parse", "HEAD"], text=True).strip()
provenance["git_branch"] = subprocess.check_output(
["git", "branch", "--show-current"], text=True).strip()
provenance["merge_base"] = subprocess.check_output(
["git", "merge-base", "HEAD", "origin/main"], text=True).strip()
provenance["commits_ahead_of_main"] = int(subprocess.check_output(
["git", "rev-list", "--count", "origin/main..HEAD"], text=True).strip())
provenance["diff_stat_vs_main"] = subprocess.check_output(
["git", "diff", "--stat", "origin/main...HEAD"], text=True).strip()
# Note for forks: ensure current main is tracked (usually origin/main for personal forks).
# If using an upstream remote, adapt the branch names to match (e.g., upstream/main).
# === SERVER RUNTIME (MANDATORY for server tests) ===
port = BASE_URL.split(":")[-1].rstrip("/")
pids = subprocess.check_output(
["lsof", "-i", f":{port}", "-t"], text=True).strip().split("\n")
provenance["server"] = {
"pid": pids[0] if pids else None,
"port": port,
"process_cmdline": subprocess.check_output(
["ps", "-p", pids[0], "-o", "command="], text=True).strip() if pids else None,
"env_vars": {var: os.environ.get(var) for var in
["WORLDAI_DEV_MODE", "TESTING", "GOOGLE_APPLICATION_CREDENTIALS"]}
}
return provenance
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 · 1,240 lines · 27 tokens per session scan A 05b2900e4729
evidence-standards is a skill published in the GitHub repository jleechanorg/agent-orchestrator-ts (8 stars, last pushed 3d ago), licensed MIT. It adds 27 tokens to every session and 10,857 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.
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