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 skills/danshapiro/kilroy/build-dodnpx skills add danshapiro/kilroy --skill build-dodgit clone --depth 1 https://github.com/danshapiro/kilroyWrote 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/danshapiro/kilroy/build-dod)<a href="https://agentmods.dev/skills/danshapiro/kilroy/build-dod"><img src="https://agentmods.dev/badge/skills/danshapiro/kilroy/build-dod.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.02229 |
| Opus 5 | $0.00014 | $0.01115 |
| Sonnet 5 | $0.00006 | $0.00446 |
| Haiku 4.5 | $0.00003 | $0.00223 |
Grade A, and why
build-dod 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 4d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build DoD
A DoD converts a spec into pass/fail gates. Its power is in integration tests — scenarios that prove the deliverable works by exercising it the way a user would.
Core Principle
Tests aren't there to be passed. They're there to prove results. Verify the deliverable through integration scenarios that exercise it end-to-end, not through unit tests that verify internals.
Process
- Read the full spec
- List deliverables — the artifacts that exist when done
- If a digraph/flow diagram is provided, extract intended user journeys, decision points, and outcomes from it
- Write acceptance criteria — one observable assertion per row
- Inventory every user-facing message surface from the spec
- Write integration test scenarios that prove the deliverable works end-to-end
- Map each AC and each message to the scenario(s) that prove it
- Crosscheck — confirm every AC and every message is covered and every scenario is sound
When this skill is used inside an Attractor run, scratch outputs should be written under .ai/runs/$KILROY_RUN_ID/.... Root .ai is not implicitly ingested.
If a digraph is provided
Use the graph in two passes:
- Intent pass (primary): Treat the graph as a map of product intent and user flow. Use it to identify the major journeys, decisions, and failure/recovery paths that matter to users.
- Flow sanity pass (secondary): Do lightweight topology checks only to catch intent-breaking issues (for example, a required outcome has no reachable path).
Acceptance Criteria
Each AC is a single, testable assertion using observable language: "exists", "returns", "displays", "produces", "exits 0".
Group by concern (e.g. Build, Output, Behavior, Integration). Number hierarchically: AC-1.1, AC-1.2, AC-2.1.
ACs describe what must be true. They are proven by integration test scenarios, not by individual unit tests.
Integration Test Scenarios
Integration tests are the primary verification mechanism. Each scenario exercises the delivered artifact directly, proving multiple acceptance criteria simultaneously.
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.
- 4d ago First seen · 212 lines · 28 tokens per session scan A 67a1852ada57
build-dod is a skill published in the GitHub repository danshapiro/kilroy (218 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 2,229 once invoked, about $0.0001 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 2026-08-30.
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