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 agentmods add skills/alonf/mcppythondemo/parity-auditnpx skills add alonf/MCPPythonDemo --skill parity-auditgit clone --depth 1 https://github.com/alonf/MCPPythonDemoWhat 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 | $0.00017 | $0.00253 |
| Opus 5 | $0.00009 | $0.00127 |
| Sonnet 5 | $0.00003 | $0.00051 |
| Haiku 4.5 | $0.00002 | $0.00025 |
Grade A, and why
parity-audit 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 yesterday.
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.
What it actually says
Parity Audit
Use when
- A migrated implementation looks "more complex" than the reference
- You need to tell whether that complexity is required for behavioral parity or just convenience/portability work
Method
- Inspect the reference branch's runnable entrypoints, not just summaries.
- Identify the behavioral contract:
- transport
- server/client split
- LLM involvement
- tool exposure/orchestration
- credential model
- Mark everything in the target implementation as either:
- parity-critical
- ergonomic/portability add-on
- Explain any extra complexity in human terms: "hidden by the original SDK" vs "new convenience layer".
Example from this repo
- Parity-critical: Python tool-schema translation + tool-call loop, because C# M1 uses
AsAIAgent(... tools: [.. tools]). - Extra ergonomics:
.env.local, CLI overrides, env alias lookup, API-key fallback, interactive chat polish.
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.
- yesterday First seen · 32 lines · 17 tokens per session scan A 86c4b442c5e8
parity-audit is a skill published in the GitHub repository alonf/MCPPythonDemo (0 stars, last pushed 4mo ago), licensed MIT. It adds 17 tokens to every session and 253 once invoked, about $0.0001 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
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…