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 d-mariano/spicyclaude --skill feature-integrationgit clone --depth 1 https://github.com/d-mariano/spicyclaudeWrote 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/d-mariano/spicyclaude/feature-integration)<a href="https://agentmods.dev/skills/d-mariano/spicyclaude/feature-integration"><img src="https://agentmods.dev/badge/skills/d-mariano/spicyclaude/feature-integration/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/d-mariano/spicyclaude/feature-integration"><img src="https://agentmods.dev/badge/skills/d-mariano/spicyclaude/feature-integration.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 | $0.00046 | $0.02323 |
| Opus 5 | $0.00023 | $0.01162 |
| Sonnet 5 | $0.00009 | $0.00465 |
| Haiku 4.5 | $0.00005 | $0.00232 |
Grade A, and why
feature-integration 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.
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Integration Workflow
You are executing a multi-phase technical design workflow for adding a feature to an existing codebase. The hard problem is understanding what exists well enough to extend it without breaking it.
Before You Start
Read the example output at .claude/skills/feature-integration/examples/webhook-delivery.md to calibrate the expected depth, format, and level of concreteness. Your output should match this quality bar.
If the user's task involves significant restructuring or replacement of existing code, also read .claude/skills/refactor-modifier/SKILL.md and apply its additions at each phase (look for "Phase 1 Addition", "Phase 2 Addition", etc.).
Critical Rules
- Pause after every phase. Present your output, then ask the user to review before proceeding.
- Read the actual code. Do not trust assumptions. Use Grep, Glob, Read, and Bash to explore the codebase. Read config files, key services, existing tests, and similar features.
- Frame everything as deltas. This is NOT a greenfield design. For existing components, describe what changes, not what they are. For new components, describe them fully but note which existing pattern they follow.
- Follow existing conventions. Match the naming, structure, and patterns of the codebase even if you'd do it differently. Consistency beats local perfection.
- The output file must stand alone. A downstream planner or engineer should be able to read it cold.
- Save intermediate outputs. Write Phase 1 and Phase 2 reports to
docs/design/<task-slug>/phase-1-recon.mdanddocs/design/<task-slug>/phase-2-strategy.mdrespectively. The final design goes todocs/design/<task-slug>/design.md.
Phase 1: Codebase Reconnaissance
Goal: Develop deep understanding of the existing system's structure, patterns, and the specific areas the feature will touch. Do NOT design anything yet.
Start by actually reading the codebase:
- Run
find . -maxdepth 3 -type f | head -150andtree -L 2 -dto map structure - Read package manifests (package.json, go.mod, pyproject.toml, Cargo.toml, *.csproj, etc.)
- Read existing architecture docs if present (ARCHITECTURE.md, docs/, README.md)
- Read 2-3 features similar in shape to what we're building
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.
- 12d ago First seen · 229 lines · 46 tokens per session scan A c11cbbf24f44
feature-integration is a skill published in the GitHub repository d-mariano/spicyclaude (5 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 2,323 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 2026-08-31.
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