Borrowing it
Nothing to install: this file belongs to abuango/pos-ai. 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/abuango/pos-ai/main/.claude/skills/feature-spec/SKILL.mdgit clone --depth 1 https://github.com/abuango/pos-aiWrote 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/abuango/pos-ai/feature-spec)<a href="https://agentmods.dev/skills/abuango/pos-ai/feature-spec"><img src="https://agentmods.dev/badge/skills/abuango/pos-ai/feature-spec.svg" alt="Measured on agentmods" 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 | $0.01143 |
| Opus 5 | $0.00028 | $0.00571 |
| Sonnet 5 | $0.00011 | $0.00229 |
| Haiku 4.5 | $0.00006 | $0.00114 |
Grade A, and why
feature-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 8d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Spec Skill
Setup
Before starting: check .handoff/sessions/ for active sessions, read context status.yaml, run git status. Follow .rules/universal.md (Plan -> Approve -> Execute).
You create persistent feature specification documents. Specs are the source of truth that survive across sessions — they prevent context loss, scope creep, and misaligned implementations.
Process
Step 1: Interview
Before writing the spec, clarify with the user:
- What problem does this solve? — Not what to build, but why
- Who is the user? — Which user type/persona benefits
- What does success look like? — How do we know it's working
- What's out of scope? — Explicit boundaries prevent creep
- Any constraints? — Timeline, technology, compatibility requirements
If the user provides a complete description, extract these answers from their description rather than asking.
Step 2: Research Existing Context
- Check for existing specs —
ls {project_path}/docs/specs/ - Check related features — Are there specs this feature depends on or affects?
- Check the codebase — What already exists that this feature touches?
- Check the data model — What entities are involved?
Step 3: Write the Spec
Use the template below. Every section is mandatory — if a section doesn't apply, explicitly state "N/A" with a reason.
Step 4: Identify Ripple Effects
Check if this spec affects other existing specs:
- Does it change a shared data model?
- Does it affect an API contract?
- Does it change user flows documented elsewhere?
If yes, note which specs need updating.
Spec Template
Save to: {project_path}/docs/specs/{feature-name}.md
# Feature Spec: {Feature Name}
**Status:** Draft | Approved | In Progress | Complete | Deprecated
**Author:** {who}
**Date:** {DATE}
**Last Updated:** {DATE}
**Project:** {project name}
---
## Problem Statement
{What problem exists? Why does it matter? What's the cost of not solving it?}
## User Story
As a {user type}, I want to {action}, so that {benefit}.
## Requirements
### Must Have
1. {Requirement — specific, testable}
2. {Requirement}
### Should Have
1. {Requirement}
### Won't Have (Explicit Scope Exclusions)
1. {What this feature explicitly does NOT include, and why}
## Design
### User Flow
1. User {action}
2. System {response}
3. User sees {outcome}
### Data Model Changes
{New tables, columns, or relationships needed}
| Table | Column | Type | Notes |
|-------|--------|------|-------|
| {table} | {column} | {type} | {constraints, defaults} |
### API Changes
{New or modified endpoints}
| Method | Endpoint | Request | Response | Auth |
|--------|----------|---------|----------|------|
| POST | /api/v1/{resource} | `{ field: type }` | `{ data: ... }` | Required |
### UI Changes
{Screens or components affected — describe layout and behavior}
## Edge Cases
1. **{Edge case}** — {How it should be handled}
2. **{Edge case}** — {How it should be handled}
## Dependencies
- **Internal:** {Other features or services this depends on}
- **External:** {Third-party APIs, libraries, or services}
## Acceptance Criteria
- [ ] {Testable criterion 1}
- [ ] {Testable criterion 2}
- [ ] {Testable criterion 3}
## Open Questions
- [ ] {Question that needs answering before implementation}
---
## Changelog
| Date | Author | Change |
|------|--------|--------|
| {DATE} | {who} | Initial draft |
What ships with it
1 file 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.
- 8d ago First seen · 157 lines · 55 tokens per session scan A 6fd19b558c77
feature-spec is a skill published in the GitHub repository abuango/pos-ai (2 stars, last pushed 5mo ago), licensed MIT. It adds 55 tokens to every session and 1,143 once invoked, about $0.0003 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 2026-08-31.
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