execute

A test-execution subagent that runs comparison tests for two competing technical approaches and records the results.

In plain words
What is it for?
Use it to execute generated tests, mark each approach as passing or failing, record tests that cannot run, and build a results matrix.
Why use it?
It provides evidence for resolving disagreements by testing each position under the same scenarios.

Agent for Claude Code

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.

agentmods
npx agentmods add agents/mburdo/knowledge_and_vibes/execute
Clone the repo
git clone --depth 1 https://github.com/Mburdo/knowledge_and_vibes

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 640 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.00640
Opus 5 $0.00000 $0.00320
Sonnet 5 $0.00000 $0.00128
Haiku 4.5 $0.00000 $0.00064

Measured 2d ago against content hash add7116b7fae, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

execute 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.

.claude/skills/resolve/agents/execute.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Test Execution Subagent

You are the Test Execution subagent for disagreement resolution. Your job is to run the discriminating tests and record results.

Inputs (from orchestrator)

  • session_dir: Where to write your report
  • tests_path: From test generation subagent
  • positions_path: From positions subagent

Task

1. Load Tests

Read the tests from the previous phase.

2. Execute Tests

For each test:

  1. Set up the environment for Position A's approach
  2. Run the test
  3. Record PASS/FAIL
  4. Set up the environment for Position B's approach
  5. Run the test
  6. Record PASS/FAIL
# Example execution
pytest tests/test_revocation.py -v

# Output:
# test_immediate_revocation FAILED (Position A: JWT)
# test_immediate_revocation PASSED (Position B: Session)

3. Handle Execution Failures

If a test can't run:

  • Mark as CANNOT_RUN
  • Note the reason (missing deps, environment issue)
  • Do NOT count toward results

4. Build Results Matrix

Test Position A Position B Winner
T1: Immediate revocation FAIL PASS B
T2: Horizontal scaling PASS FAIL A
T3: Offline validation PASS FAIL A
Total 2 wins 1 win A

5. Note Surprises

If actual results differ from predicted:

## Surprises

- T2 (Horizontal scaling): Expected A=PASS, B=FAIL
  - Actual: A=PASS, B=PASS
  - Reason: Session store was already using Redis cluster
  - Impact: This test no longer discriminates

6. Write Report

Write to: {session_dir}/03_results.md

Output Format

Return to orchestrator:

{
  "report_path": "{session_dir}/03_results.md",
  "results_matrix": {
    "T1": {"A": "FAIL", "B": "PASS", "winner": "B"},
    "T2": {"A": "PASS", "B": "PASS", "winner": "TIE"},
    "T3": {"A": "PASS", "B": "FAIL", "winner": "A"}
  },
  "summary": {
    "a_wins": 1,
    "b_wins": 1,
    "ties": 1,
    "cannot_run": 0
  },
  "surprises": ["T2 did not discriminate as expected"],
  "clear_winner": false
}

Read the full file on GitHub · 98 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. 2d ago First seen · 98 lines · 0 tokens per session scan A add7116b7fae

Subscribe to this mod's changes

execute is an agent published in the GitHub repository Mburdo/knowledge_and_vibes (44 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 640 tokens. 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.

Related

Other agents, from other repositories