Borrowing it
Nothing to install: this file belongs to takumi0706/google-calendar-mcp. 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/takumi0706/google-calendar-mcp/main/.claude/skills/kiro-validate-impl/SKILL.mdgit clone --depth 1 https://github.com/takumi0706/google-calendar-mcpWrote 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/takumi0706/google-calendar-mcp/kiro-validate-impl)<a href="https://agentmods.dev/skills/takumi0706/google-calendar-mcp/kiro-validate-impl"><img src="https://agentmods.dev/badge/skills/takumi0706/google-calendar-mcp/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/takumi0706/google-calendar-mcp/kiro-validate-impl"><img src="https://agentmods.dev/badge/skills/takumi0706/google-calendar-mcp/kiro-validate-impl.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.02458 |
| Opus 5 | $0.00015 | $0.01229 |
| Sonnet 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 12d 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 — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
kiro-validate-impl Skill
Role
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
Core Mission
- 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 (mock/stub detection)
- 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?
Execution Steps
Step 1: Detect Validation Target
If no arguments provided:
- Parse conversation history for
/kiro-implcommands to detect recently implemented features and tasks - Scan
.kiro/specs/for features with completed tasks[x] - Report detected implementations (e.g., "user-auth: 1.1, 1.2, 1.3")
If feature provided (feature specified, tasks empty):
- Use specified feature
- Detect all completed tasks
[x]in.kiro/specs/{feature}/tasks.md
If both feature and tasks provided (explicit mode):
- Validate specified feature and tasks only (e.g.,
user-auth 1.1,1.2)
Step 2: Gather Context
If steering/spec context is already available from conversation, skip redundant file reads. Otherwise, for each detected feature:
- Read
.kiro/specs/<feature>/spec.jsonfor metadata - Read
.kiro/specs/<feature>/requirements.mdfor requirements - Read
.kiro/specs/<feature>/design.mdfor design structure - Read
.kiro/specs/<feature>/tasks.mdfor task list and Implementation Notes - Core steering context:
product.md,tech.md,structure.md - Additional steering files only when directly relevant to the validated boundaries, runtime prerequisites, integrations, domain rules, security/performance constraints, or team conventions that affect the GO/NO-GO call
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.
- 12d ago First seen · 205 lines · 31 tokens per session scan A fb17e2c5eaa4
kiro-validate-impl is a skill published in the GitHub repository takumi0706/google-calendar-mcp (59 stars, last pushed 25d ago), licensed MIT. It adds 31 tokens to every session and 2,458 once invoked, about $0.0002 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.
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.
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".
neuron-evaluation-engineer
Create and run AI evaluations with datasets, assertions, and output drivers in Neuron AI. Use this skill whenever the user mentions evaluation, testing AI systems, creating evaluators, dataset-driven testing, assertion-based validation, or wants to measure AI system performance. Also trigger for tasks involving…
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.
skill-benchmark
Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.