Borrowing it
Nothing to install: this file belongs to standardbeagle/mcp-tui. 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/standardbeagle/mcp-tui/main/.claude/skills/write-tech-spec/SKILL.mdgit clone --depth 1 https://github.com/standardbeagle/mcp-tuiWrote 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/standardbeagle/mcp-tui/write-tech-spec)<a href="https://agentmods.dev/skills/standardbeagle/mcp-tui/write-tech-spec"><img src="https://agentmods.dev/badge/skills/standardbeagle/mcp-tui/write-tech-spec/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/standardbeagle/mcp-tui/write-tech-spec"><img src="https://agentmods.dev/badge/skills/standardbeagle/mcp-tui/write-tech-spec.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 | $0.00068 | $0.01958 |
| Opus 5.5 | $0.00027 | $0.00783 |
| Sonnet 5.5 | $0.00014 | $0.00392 |
| Haiku 4.5 | $0.00007 | $0.00196 |
Grade A, and why
write-tech-spec 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 1mo 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 — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write Technical Specification
Create a technical specification for a component, feature, or architecture decision. Tech specs are the bridge between requirements (user stories) and implementation (code). They answer "how" and "why" before code is written.
Pre-Flight Checks
- Confirm what needs to be specified with the user
- Read
.claude/rules/architecture.mdfor active decisions and constraints - Read
.claude/rules/documentation.mdfor documentation standards - Identify related user stories or requirements
- Determine spec type: Component Spec, Feature Spec, or ADR
Spec Type Selection
Component Spec
For new components or significant changes to existing components:
- A new service, module, or subsystem
- A significant refactoring of an existing component
- A new integration with an external system
Feature Spec
For features that span multiple components:
- A new user-facing capability
- A cross-cutting concern (auth, logging, caching)
- A feature that changes multiple existing components
ADR (Architecture Decision Record)
For significant architectural decisions:
- Technology choices (framework, database, library)
- Pattern adoption (event sourcing, CQRS, microservices)
- Infrastructure decisions (hosting, deployment, scaling)
- Migration decisions (old pattern to new pattern)
Component Spec
Format
# Component: [Name]
## Status: [Draft | Review | Approved | Implemented]
## Purpose
[One sentence: what does this component do and why does it exist?]
## Context
[What problem does this solve? What existing code does it replace or extend?]
## Interface
### Public API
| Method/Function | Input | Output | Description |
|----------------|-------|--------|-------------|
| [name] | [params with types] | [return type] | [what it does] |
### Events Emitted
| Event | Payload | When |
|-------|---------|------|
| [name] | [data shape] | [trigger condition] |
### Events Consumed
| Event | Source | Action |
|-------|--------|--------|
| [name] | [context] | [what this component does] |
## Dependencies
### Required
| Dependency | Purpose | Interface |
|-----------|---------|-----------|
| [name] | [why needed] | [how accessed] |
### Optional
| Dependency | Purpose | Fallback |
|-----------|---------|----------|
| [name] | [why useful] | [behavior when absent] |
## Data Model
### State Shape
[Key data structures, schemas, types]
### Persistence
[How and where state is stored — database table, cache, file, memory]
### Migrations
[If this changes existing data, what migration is needed?]
## Behavior
### Core Algorithm / Logic
[How the component works — decision logic, transformations, state transitions]
### Side Effects
[What I/O does this component perform? Isolated at boundaries per architecture rules.]
### Concurrency
[Thread safety, race conditions, ordering guarantees]
## Error Handling
| Error Condition | Detection | Recovery | User Impact |
|----------------|-----------|----------|-------------|
| [what fails] | [how detected] | [how handled] | [what user sees] |
## Performance
- Expected throughput: [requests/sec, items/sec]
- Latency target: [p50, p95, p99]
- Resource limits: [memory, connections, file handles]
- Scaling approach: [horizontal, vertical, none]
## Security
- Authentication: [how callers are authenticated]
- Authorization: [what permissions are required]
- Data sensitivity: [PII, secrets, financial data]
- Attack surface: [input validation, injection prevention]
## Testing Strategy
| Tier | What to Test | Approach |
|------|-------------|----------|
| Unit | Pure logic, validation, transformations | Direct function calls, no mocks |
| Integration | Data access, external service calls | Real database, replay proxies |
| E2E | User-facing behavior | Full stack, highest fidelity |
## Open Questions
[Anything unresolved that needs input before implementation]
## Related
- User Stories: [US-NNN]
- User Flows: [flow links]
- ADRs: [ADR-NNN]
- Bounded Context: [context name]
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.
- 1mo ago First seen · 312 lines · 68 tokens per session scan A b73a2eeec36b
write-tech-spec is a skill published in the GitHub repository standardbeagle/mcp-tui (12 stars, last pushed 5d ago), licensed MIT. It adds 68 tokens to every session and 1,958 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-28.
Other skills, from other repositories
analyze-codebase
Run comprehensive PLG analysis on a codebase to detect tech stack, existing growth features, and revenue opportunities. Use when the user says "analyze", "scan", "audit codebase", or "find growth opportunities".
build-implementation
Generate context-aware implementation prompts for a selected growth loop. Use when the user says "build", "implement", "generate code", "create prompt", or "how do I build this".
ai-session-search
Search, recover, inspect, export, and analyze local AI session history with AI Session Search (aise) across Claude Code, Claude Desktop local agent, Codex, Cursor, Antigravity, Pi coding agent, Prime Agent, Google AI Studio, and Gemini CLI. Use when asked to "find prior AI work", "recover context after compaction"…
deploy-telemetry
Set up analytics and tracking infrastructure for growth loops. Use when the user says "deploy telemetry", "set up analytics", "tracking", "events", "push to supabase", or "skene push".
plan-growth-loop
Generate prioritized growth loops with implementation roadmaps based on codebase analysis. Use when the user says "plan", "growth loops", "prioritize", "what should I build", or "roadmap".
validate-loop
Check if growth loop requirements are actually implemented in the codebase. Use when the user says "validate", "check status", "skene status", "is it done", or "verify implementation".