check-performance

A code-review check for work that runs repeatedly or must meet a time or cost limit. It looks for memory allocation, locking, and work that grows too much as input grows.

In plain words
What is it for?
Use it to review performance-sensitive modules, such as audio, video, input, per-frame, query, and data-scanning code.
Why use it?
It helps catch code that is functionally correct but misses real-time deadlines, exceeds budgets, or slows down on large inputs.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/leifericf/agentic-sdk/check-performance
Any agent
npx skills add leifericf/agentic-sdk --skill check-performance
Clone the repo
git clone --depth 1 https://github.com/leifericf/agentic-sdk

Made for: Claude Code, Codex.

Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 923 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00030 $0.00923
Opus 5 $0.00015 $0.00462
Sonnet 5 $0.00006 $0.00185
Haiku 4.5 $0.00003 $0.00092

Measured 2d ago against content hash b3b1a9926fa7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

check-performance 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 2d 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.

skills/check-performance/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

check-performance

Role: review the shard against the project's performance targets.

Failure model: the code is correct but breaks a real-time or budget commitment, allocates on a hot path, or does work that grows worse than linearly with input the caller controls.

Performance targets are project-specific. Read the design docs and the descriptor for the project's budgets (frame time, callback latency, query cost, scan throughput) before sweeping. What follows is the sweep pattern, not the budget.

Look for

  1. Allocation on hot paths. A real-time callback (audio, video, input) or a per-frame function that allocates on the steady path: no incidental allocation, no internal collection growth, no formatting inside the loop. A per-keystroke query path must not allocate per call beyond the result vector. Any allocation in these paths is a finding.
  2. Locks on hot paths. A lock held across an unbounded operation on a real-time or per-frame path. Cross-thread communication on a hot path belongs on a lock-free queue or an atomic, not a mutex.
  3. Arithmetic that defeats SIMD or the hardware. Inner loops over sampled data written as scalar code when the platform's vector type would do; mixed precision inside a hot loop that forces a conversion per iteration. Vectorization is not always the right answer; the choice must be deliberate, and a benchmark wins the argument.
  4. Unbounded work from unbounded input. A scan that processes a whole set synchronously without yielding; a decode that loads the whole payload before streaming; an analysis whose runtime grows worse than linearly with input length; a layout that recomputes from scratch on every change.
  5. Query and index efficiency. A query that scans the whole set when an index would do; a filter that re-realizes a lazy sequence on every access; a lookup that walks a list when a set or map would do; a sort or projection recomputed when the input has not changed.
  6. Waste in a render or diff pipeline. A per-frame allocation in a diff path; a uniform or buffer update that re-uploads static data; a descriptor or command buffer rebuilt when a single binding changed.
  7. Throughput on a scan or batch path. A scan that reads the whole payload to compute a value the header would yield; a batch that reworks items whose input has not changed (a content hash is the gate); a batch that holds a shared lock for its whole duration.

Read the full file on GitHub · 94 lines

Changes

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.

  1. 2d ago First seen · 94 lines · 30 tokens per session scan A b3b1a9926fa7

Subscribe to this mod's changes

check-performance is a skill published in the GitHub repository leifericf/agentic-sdk (5 stars, last pushed 13d ago), licensed MIT. It adds 30 tokens to every session and 923 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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