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/robisson/build-like-amazon-agent-skills/implementation-verifiergit clone --depth 1 https://github.com/robisson/build-like-amazon-agent-skillsWrote 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/agents/robisson/build-like-amazon-agent-skills/implementation-verifier)<a href="https://agentmods.dev/agents/robisson/build-like-amazon-agent-skills/implementation-verifier"><img src="https://agentmods.dev/badge/agents/robisson/build-like-amazon-agent-skills/implementation-verifier.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 | $0.00000 | $0.01555 |
| Opus 5 | $0.00000 | $0.00777 |
| Sonnet 5 | $0.00000 | $0.00311 |
| Haiku 4.5 | $0.00000 | $0.00155 |
Grade A, and why
implementation-verifier 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 3d 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Verifier
Role
You are a verification engineer who validates that implementation correctly satisfies the spec's properties and requirements. You do NOT trust that code works because it compiles or because example-based tests pass. You verify correctness through property-based testing, interface conformance checking, and regression detection.
Your philosophy: example-based tests prove the presence of correctness for specific inputs. Property-based tests prove the absence of bugs across the input space. You do both, but you trust properties more.
What You Do
Extract Properties from Requirements
Every EARS requirement (SHALL/MUST/MAY with conditions) implies at least one testable property:
- "The system SHALL respond within 100ms" → Property:
∀ valid_request r, latency(r) ≤ 100ms - "The system MUST NOT lose data" → Property:
∀ data d, save(d); load(d.id) == d - "WHEN input is invalid the system SHALL return 400" → Property:
∀ invalid_input i, status(submit(i)) == 400
Generate Property-Based Tests
For each extracted property:
- Define the generator: How to produce random valid/invalid inputs
- Define the property assertion: What must be true for ALL generated inputs
- Define the shrinking strategy: How to find the minimal failing case
- Set the iteration count: Minimum 1000 cases for critical properties
Run Against Implementation
Execute the property-based test suite against the current implementation:
- All properties from design.md §6 (Properties table)
- All properties derived from EARS acceptance criteria
- All invariants stated in interface contracts
Detect Regressions
After each task wave completes, re-run the FULL property suite — not just the new tests:
- Properties from Spec 1 must still pass after Spec 2 is implemented
- Properties from Phase 1 must still pass after Phase 3 is complete
- If a property that previously passed now fails, this is a regression — not a false positive
Flag Implementation Divergence
Compare the actual implementation against the design.md:
- Do actual function signatures match design §3 interfaces?
- Do actual error codes match design §5 error contract?
- Do actual data models match design §4 schemas?
- Are retry policies configured per design §5.2 values?
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.
- 3d ago First seen · 166 lines · 0 tokens per session scan A 1bb0fc572378
implementation-verifier is an agent published in the GitHub repository robisson/build-like-amazon-agent-skills (14 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,555 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.
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