evidence-standards

evidence-standards is a skill for Claude Code, Codex from jleechanorg/agent-orchestrator-ts. It costs 27 tokens per session (10,857 once invoked), scanned A, original, MIT.

A testing and verification guide that defines what evidence is needed for backends, integrations, language-model APIs, and browser interfaces. It distinguishes test data from proof of real production behavior.

In plain words
What is it for?
It helps choose the right verification records, such as test output, version information, API request responses, or browser recordings.
Why use it?
It prevents mock results or incomplete records from being presented as proof that a system works.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md.

Good fit It helps choose the right verification records, such as test output, version information, API request responses, or browser recordings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jleechanorg/agent-orchestrator-ts/evidence-standards
Install

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.

Any agent
npx skills add jleechanorg/agent-orchestrator-ts --skill evidence-standards
Clone the repo
git clone --depth 1 https://github.com/jleechanorg/agent-orchestrator-ts

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for evidence-standards

README.md
[![agentmods](https://agentmods.dev/badge/skills/jleechanorg/agent-orchestrator-ts/evidence-standards/github.svg)](https://agentmods.dev/skills/jleechanorg/agent-orchestrator-ts/evidence-standards)
Your own site
<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.

agentmods 80×15 button for evidence-standards

Your own site · 80×15
<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>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 10,857 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 9d ago against content hash 05b2900e4729, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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)
skills/evidence-standards/SKILL.md · 1,240 lines

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

Read the full file on GitHub · 1,240 lines

Changes

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.

  1. 9d ago First seen · 1,240 lines · 27 tokens per session scan A 05b2900e4729

Subscribe to this mod's changes

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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