Borrowing it
Nothing to install: this file belongs to akaghef/M3E. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/akaghef/M3E/main/.agents/skills/kiro-validate-impl/SKILL.mdgit clone --depth 1 https://github.com/akaghef/M3EWrote 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/akaghef/m3e/kiro-validate-impl)<a href="https://agentmods.dev/skills/akaghef/m3e/kiro-validate-impl"><img src="https://agentmods.dev/badge/skills/akaghef/m3e/kiro-validate-impl/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/akaghef/m3e/kiro-validate-impl"><img src="https://agentmods.dev/badge/skills/akaghef/m3e/kiro-validate-impl.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 | $0.00031 | $0.02459 |
| Opus 5.5 | $0.00012 | $0.00984 |
| Sonnet 5.5 | $0.00006 | $0.00492 |
| Haiku 4.5 | $0.00003 | $0.00246 |
Grade A, and why
kiro-validate-impl 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 5d 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.
This is a copy
88% identical to kiro-validate-impl — 27 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Integration Validation
<background_information> Individual tasks have already been reviewed by the per-task reviewer during implementation. Your job is to catch problems that only become visible when looking across all tasks together.
Boundary terminology continuity:
-
discovery identifies
Boundary Candidates -
design fixes
Boundary Commitments -
tasks constrain execution with
_Boundary:_ -
feature validation checks for cross-task
Boundary Violations -
Success Criteria:
- All tasks marked
[x]in tasks.md - Full test suite passes (not just per-task tests)
- Cross-task integration works (data flows between components, interfaces match)
- Requirements coverage is complete across all tasks (no gaps between tasks)
- Design structure is reflected end-to-end (not just per-component)
- No orphaned code, conflicting implementations, integration seams, or boundary spillover
- All tasks marked
What This Skill Does NOT Do: Per-task checks are the reviewer's responsibility during $kiro-impl. This skill does NOT re-check individual task acceptance criteria, per-file reality checks, or single-task spec alignment.
This skill's main question is: when the completed tasks are viewed together, do they still respect the designed boundary seams and dependency direction? </background_information>
1. Detect Validation Target
If no arguments provided ($1 empty):
- Parse conversation history for
$kiro-impl <feature> [tasks]commands - Extract feature names and task numbers from each execution
- Aggregate all implemented tasks by feature
- Report detected implementations (e.g., "user-auth: 1.1, 1.2, 1.3")
- If no history found, scan
.kiro/specs/for features with completed tasks[x]
If feature provided ($1 present, $2 empty):
- Use specified feature
- Detect all completed tasks
[x]in.kiro/specs/$1/tasks.md
If both feature and tasks provided ($1 and $2 present):
- Validate specified feature and tasks only (e.g.,
user-auth 1.1,1.2)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 206 lines · 31 tokens per session scan A cdc68cb4d78b
kiro-validate-impl is a skill published in the GitHub repository akaghef/M3E (11 stars, last pushed 5d ago), licensed MIT. It adds 31 tokens to every session and 2,459 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to kiro-validate-impl, differing in 27 lines, and is treated as a copy.
Other skills, from other repositories
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
eval-dataset-design
A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.
tika-eval-compare
Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".
cua-driver
Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.
jetson-validate-image
Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.
atmos-validation
Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.