Borrowing it
Nothing to install: this file belongs to shashankswe2020-ux/whoop-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/shashankswe2020-ux/whoop-mcp/main/.github/skills/documentation-and-adrs/SKILL.mdgit clone --depth 1 https://github.com/shashankswe2020-ux/whoop-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/shashankswe2020-ux/whoop-mcp/documentation-and-adrs)<a href="https://agentmods.dev/skills/shashankswe2020-ux/whoop-mcp/documentation-and-adrs"><img src="https://agentmods.dev/badge/skills/shashankswe2020-ux/whoop-mcp/documentation-and-adrs/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/shashankswe2020-ux/whoop-mcp/documentation-and-adrs"><img src="https://agentmods.dev/badge/skills/shashankswe2020-ux/whoop-mcp/documentation-and-adrs.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 | $0.00043 | $0.01926 |
| Opus 5 | $0.00022 | $0.00963 |
| Sonnet 5 | $0.00009 | $0.00385 |
| Haiku 4.5 | $0.00004 | $0.00193 |
Grade A, and why
documentation-and-adrs 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- documentation-and-adrs — 100% identical, 0 lines differ
- documentation-and-adrs — 100% identical, 55 lines differ
- documentation-and-adrs — 100% identical, 0 lines differ
- documentation-and-adrs — 100% identical, 0 lines differ
- documentation-and-adrs — 100% identical, 0 lines differ
- documentation-and-adrs — 100% identical, 0 lines differ
- documentation-and-adrs — 100% identical, 4 lines differ
- documentation-and-adrs — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation and ADRs
Overview
Document decisions, not just code. The most valuable documentation captures the why — the context, constraints, and trade-offs that led to a decision. Code shows what was built; documentation explains why it was built this way and what alternatives were considered. This context is essential for future humans and agents working in the codebase.
When to Use
- Making a significant architectural decision
- Choosing between competing approaches
- Adding or changing a public API
- Shipping a feature that changes user-facing behavior
- Onboarding new team members (or agents) to the project
- When you find yourself explaining the same thing repeatedly
When NOT to use: Don't document obvious code. Don't add comments that restate what the code already says. Don't write docs for throwaway prototypes.
Architecture Decision Records (ADRs)
ADRs capture the reasoning behind significant technical decisions. They're the highest-value documentation you can write.
When to Write an ADR
- Choosing a framework, library, or major dependency
- Designing a data model or database schema
- Selecting an authentication strategy
- Deciding on an API architecture (REST vs. GraphQL vs. tRPC)
- Choosing between build tools, hosting platforms, or infrastructure
- Any decision that would be expensive to reverse
ADR Template
Store ADRs in docs/decisions/ with sequential numbering:
# ADR-001: Use PostgreSQL for primary database
## Status
Accepted | Superseded by ADR-XXX | Deprecated
## Date
2025-01-15
## Context
We need a primary database for the task management application. Key requirements:
- Relational data model (users, tasks, teams with relationships)
- ACID transactions for task state changes
- Support for full-text search on task content
- Managed hosting available (for small team, limited ops capacity)
## Decision
Use PostgreSQL with Prisma ORM.
## Alternatives Considered
### MongoDB
- Pros: Flexible schema, easy to start with
- Cons: Our data is inherently relational; would need to manage relationships manually
- Rejected: Relational data in a document store leads to complex joins or data duplication
### SQLite
- Pros: Zero configuration, embedded, fast for reads
- Cons: Limited concurrent write support, no managed hosting for production
- Rejected: Not suitable for multi-user web application in production
### MySQL
- Pros: Mature, widely supported
- Cons: PostgreSQL has better JSON support, full-text search, and ecosystem tooling
- Rejected: PostgreSQL is the better fit for our feature requirements
## Consequences
- Prisma provides type-safe database access and migration management
- We can use PostgreSQL's full-text search instead of adding Elasticsearch
- Team needs PostgreSQL knowledge (standard skill, low risk)
- Hosting on managed service (Supabase, Neon, or RDS)
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 · 279 lines · 43 tokens per session scan A 7fed35f9c5b9
documentation-and-adrs is a skill published in the GitHub repository shashankswe2020-ux/whoop-mcp (153 stars, last pushed yesterday), licensed MIT. It adds 43 tokens to every session and 1,926 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
quick-capture
Use this skill to drop a new task into GSD Task Manager from any AI assistant that has the gsd-mcp-server connected.
triage-inbox
Use this skill to walk the user through their unfiled or stale tasks and move them into the right Eisenhower quadrant.
6502-assembly
Use when writing or debugging 6502 assembly for the Commodore PET with ca65/ld65 via pet build or pet run. Covers the PET program skeleton, the BASIC SYS stub, calling ROM routines, and 6502 gotchas.
pet-development
Use when developing, running, or debugging Commodore PET software (Commodore BASIC or 6502 assembly) on the VICE emulator with the pet CLI or the pet-tools MCP server. Covers the build/run/observe/debug loop, the stopped-state discipline, PET text encodings, and per-model differences.
6502-debugging
Use when a PET program misbehaves at runtime — crashes, corruption, wrong values, dead input, visual glitches — and you need a procedure, not a guess. Symptom-indexed playbook of runtime debugging procedures using pet-tools.
resume-parser-ats
Deeply parses resume PDFs using the OpenResume 4-step algorithm, extracts structured information (Name, Email, Phone, Education, Work Experience, Skills, etc.), evaluates ATS compatibility, and provides actionable improvement suggestions. Use when a user asks to parse, review, or analyze a resume, check…