Borrowing it
Nothing to install: this file belongs to gaoconggit/SharpPad. 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/gaoconggit/SharpPad/main/.claude/commands/kiro/validate-gap.mdgit clone --depth 1 https://github.com/gaoconggit/SharpPadWrote 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/commands/gaoconggit/sharppad/validate-gap)<a href="https://agentmods.dev/commands/gaoconggit/sharppad/validate-gap"><img src="https://agentmods.dev/badge/commands/gaoconggit/sharppad/validate-gap/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/commands/gaoconggit/sharppad/validate-gap"><img src="https://agentmods.dev/badge/commands/gaoconggit/sharppad/validate-gap.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 | $0.00009 | $0.01235 |
| Opus 5.5 | $0.00004 | $0.00494 |
| Sonnet 5.5 | $0.00002 | $0.00247 |
| Haiku 4.5 | $0.00001 | $0.00123 |
Grade A, and why
validate-gap 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 13d 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
91% identical to validate-gap — 7 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Gap Validation
Analyze implementation requirements and existing codebase for feature: $1 Specified what to analyze: $2
Context Validation
Steering Context
- Architecture context: @.kiro/steering/structure.md
- Technical constraints: @.kiro/steering/tech.md
- Product context: @.kiro/steering/product.md
- Custom steering: Load all "Always" mode custom steering files from
.kiro/steering/
Existing Spec Context
- Current spec directory: !
ls -la .kiro/specs/$1/ - Requirements document: @.kiro/specs/$1/requirements.md
- Spec metadata: @.kiro/specs/$1/spec.json
Task: Implementation Gap Analysis
Prerequisites
- Requirements document must exist:
.kiro/specs/$1/requirements.md - If not exist, stop with message: "Run
/kiro:spec-requirements $1first to generate requirements"
Analysis Process
1. Current State Investigation
Existing Codebase Analysis:
- Identify files and modules related to the feature domain
- Map current architecture patterns, conventions, and tech stack usage
- Document existing services, utilities, and reusable components
- Understand current data models, APIs, and integration patterns
Code Structure Assessment:
- Document file organization, naming conventions, and architectural layers
- Extract import/export patterns and module dependency structures
- Identify existing testing patterns (file placement, frameworks, mocking approaches)
- Map API client, database, and authentication implementation approaches currently used
- Note established coding standards and development practices
2. Requirements Feasibility Analysis
Technical Requirements Extraction:
- Parse EARS format requirements from requirements.md
- Identify technical components needed for each requirement
- Extract non-functional requirements (security, performance, etc.)
- Map business logic complexity and integration points
Gap Identification:
- Missing technical capabilities vs requirements
- Unknown technologies or external dependencies
- Potential integration challenges with existing systems
- Areas requiring research or proof-of-concept work
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.
- 13d ago First seen · 157 lines · 9 tokens per session scan A 5dc5aeb815a0
validate-gap is a command published in the GitHub repository gaoconggit/SharpPad (83 stars, last pushed 7mo ago), licensed MIT. It adds 9 tokens to every session and 1,235 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to validate-gap, differing in 7 lines, and is treated as a copy.
Other commands, from other repositories
step5-review-gate
Pipeline Step 5 — Independent review gate and drift detection. Run in a fresh agent session (read-only audit).
step4-completeness-sweep
Pipeline Step 4 — Completeness sweep to eliminate TODOs, mocks, stubs, and placeholder code before review.
code-review
../../.cratis/ai/prompts/code-review.prompt.md.
local-code-review-tests
Review uncommitted changes, build projects, and run unit tests.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.