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 skills add bybren-llc/a-safe-pulse --skill spec-creationgit clone --depth 1 https://github.com/bybren-llc/a-safe-pulseWrote 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/bybren-llc/a-safe-pulse/spec-creation)<a href="https://agentmods.dev/skills/bybren-llc/a-safe-pulse/spec-creation"><img src="https://agentmods.dev/badge/skills/bybren-llc/a-safe-pulse/spec-creation/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/bybren-llc/a-safe-pulse/spec-creation"><img src="https://agentmods.dev/badge/skills/bybren-llc/a-safe-pulse/spec-creation.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 | $0.00055 | $0.01124 |
| Opus 5 | $0.00028 | $0.00562 |
| Sonnet 5 | $0.00011 | $0.00225 |
| Haiku 4.5 | $0.00006 | $0.00112 |
Grade A, and why
spec-creation 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 6d 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
100% identical to spec-creation — 20 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec Creation Skill
TEMPLATE: This skill uses
{{PLACEHOLDER}}tokens. Replace with your project values before use.
Purpose
Guide spec creation with clear acceptance criteria, pattern references for execution agents, and testable success validation commands.
When This Skill Applies
- Creating implementation specs
- Breaking down user stories
- Defining acceptance criteria
- Adding pattern references for execution
- Creating demo scripts for validation
- Translating business requirements to technical specs
Stop-the-Line Conditions
FORBIDDEN Patterns
# FORBIDDEN: Missing acceptance criteria
## Implementation
Just do the thing.
# FORBIDDEN: No pattern reference
## Technical Approach
Build it however you want.
# FORBIDDEN: No success validation
## Done Criteria
Looks good to reviewer.
CORRECT Patterns
# CORRECT: Clear acceptance criteria
## Acceptance Criteria
- [ ] User can click button -> modal appears
- [ ] Modal shows validation errors for empty fields
- [ ] Successful submission shows success toast
# CORRECT: Pattern reference for execution
## Pattern Reference
- **UI Pattern**: `patterns_library/api/zod-validation-api.md`
- **API Pattern**: `patterns_library/api/crud-endpoint.md`
- **RLS Pattern**: `patterns_library/security/rls-user-data.md`
# CORRECT: Success validation command
## Success Validation
{{CI_VALIDATE_COMMAND}}
Spec Template (MANDATORY)
Every spec must include:
# SPEC-ASP-{number}: {Feature Name}
## Summary
{One paragraph describing the feature}
## User Story
As a [user type], I want [goal] so that [benefit].
## Acceptance Criteria
- [ ] {Testable criterion 1}
- [ ] {Testable criterion 2}
- [ ] {Testable criterion 3}
## Pattern References
- **API**: `patterns_library/api/{pattern}.md`
- **API**: `patterns_library/api/{pattern}.md`
- **Database**: `patterns_library/database/{pattern}.md`
- **Security**: Follow RLS patterns in `docs/database/RLS_IMPLEMENTATION_GUIDE.md`
## Success Validation Command
{validation command}
## Demo Script
1. Navigate to {page}
2. Click {button}
3. Observe {expected behavior}
4. Verify {success indicator}
## Logical Commits
1. `feat(scope): implement data model [ASP-{number}]`
2. `feat(scope): add API endpoint [ASP-{number}]`
3. `feat(scope): create UI component [ASP-{number}]`
4. `test(scope): add unit tests [ASP-{number}]`
What ships with it
3 files 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.
- 6d ago First seen · 188 lines · 55 tokens per session scan A 4fbf24f3fef2
spec-creation is a skill published in the GitHub repository bybren-llc/a-safe-pulse (9 stars, last pushed 5mo ago), licensed MIT. It adds 55 tokens to every session and 1,124 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to spec-creation, differing in 20 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…