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 DongDuong2001/pudo-code-system --skill performancegit clone --depth 1 https://github.com/DongDuong2001/pudo-code-systemWrote 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/dongduong2001/pudo-code-system/performance)<a href="https://agentmods.dev/skills/dongduong2001/pudo-code-system/performance"><img src="https://agentmods.dev/badge/skills/dongduong2001/pudo-code-system/performance/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/dongduong2001/pudo-code-system/performance"><img src="https://agentmods.dev/badge/skills/dongduong2001/pudo-code-system/performance.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 | $0.00014 | $0.00196 |
| Opus 5.5 | $0.00006 | $0.00078 |
| Sonnet 5.5 | $0.00003 | $0.00039 |
| Haiku 4.5 | $0.00001 | $0.00020 |
Grade A, and why
performance-debug 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.
What it actually says
Performance Debugging Skill
This skill focuses on identifying, analyzing, and resolving performance-related issues such as slow response times, CPU spikes, and UI lag.
When to use this skill
- When the application is responding slower than SLAs allow.
- When CPU usage is unexpectedly high.
- When identifying database query bottlenecks (N+1 queries, missing indexes).
Guidelines
- Measure First: Do not guess. Use profilers, APMs (Datadog, New Relic), and logging to find the bottleneck.
- Isolate the Scope: Determine if the issue is in the frontend, network, backend, or database layer.
- Algorithmic Complexity: Check for accidental O(n^2) or worse loops.
- Caching: Consider if a caching layer (Redis, Memcached) can bypass the heavy computation.
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 · 20 lines · 14 tokens per session scan A 59696fbc86ab
performance-debug is a skill published in the GitHub repository DongDuong2001/pudo-code-system (5 stars, last pushed 11d ago), licensed MIT. It adds 14 tokens to every session and 196 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
serena
Serena code intelligence — LSP-powered symbol navigation, diagnostics, and targeted code surgery. Activate before complex refactors, cross-file analysis, or when graph tools need symbol-level depth.
diagnose
Structured 6-phase debugging. Build feedback loop first, reproduce deterministically, hypothesize with ranked falsifiable theories, instrument one variable at a time, fix with regression test, cleanup. Use when a bug exists, tests fail unexpectedly, or behavior is wrong and cause is unknown.
fix
Plan-aware auto-fix loop after coding. Runs tests, lint, format, and graph checks. Updates plan task status. Use after execute/tdd.
zoom-out
One-shot module map — go up a layer of abstraction and get a domain-vocabulary module map of the codebase. Use when lost in unfamiliar code, after a long deep-dive session, or when you need to re-orient before planning.
diagnose
Diagnostic pipeline for complex/intermittent bugs. Uses diagnostics roles for Investigation, Verification, and Solution before Lead Programmer handoff. Use ONLY for non-obvious failures (root cause unclear, reproduction unstable, fixes reverted). NOT for trivial bugs with known cause — fix them directly.
systematic-debugging
Investigates bugs, failing tests, build failures, performance issues, and unexpected behavior with root-cause discipline before any fix is proposed or implemented.