GSD Pi is a command-line coding agent and project workflow system that plans, implements, verifies, and tracks software work through milestones, tasks, Git worktrees, and stored project notes. It is for developers who want structured, longer-running agent sessions using different model providers. The catalogue entries extend GSD Pi with skills and agents.
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 open-gsd/gsd-pi --skill code-optimizergit clone --depth 1 https://github.com/open-gsd/gsd-piWrote 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/open-gsd/gsd-pi/code-optimizer)<a href="https://agentmods.dev/skills/open-gsd/gsd-pi/code-optimizer"><img src="https://agentmods.dev/badge/skills/open-gsd/gsd-pi/code-optimizer/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/open-gsd/gsd-pi/code-optimizer"><img src="https://agentmods.dev/badge/skills/open-gsd/gsd-pi/code-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00094 | $0.01734 |
| Opus 5.5 | $0.00038 | $0.00694 |
| Sonnet 5.5 | $0.00019 | $0.00347 |
| Haiku 4.5 | $0.00009 | $0.00173 |
Grade A, and why
code-optimizer 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 18d 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Optimizer
Parallel multi-agent code optimization audit. Spawn 13 specialist agents simultaneously, each hunting for a different class of performance problem using pattern-based detection.
Critical Principle: No Code Reading Before Analysis
Agents MUST NOT read source files before searching for patterns. Reading the code first causes anchoring bias — the agent accepts the existing implementation as "reasonable" and misses better alternatives. Instead, each agent:
- Read its assigned reference file from
references/to load detection patterns - Use Grep/Glob to scan the codebase for anti-patterns
- For each finding, ONLY THEN read the surrounding context (5-10 lines) to confirm the issue
- Propose the optimal solution based on best practices, NOT based on the existing code
Workflow
Step 1: Detect Stack
Use Glob to identify the project's tech stack:
**/package.json→ Node.js/JS/TS (check for React, Next.js, Express, etc.)**/requirements.txt,**/pyproject.toml,**/setup.py→ Python**/go.mod→ Go**/Cargo.toml→ Rust**/pom.xml,**/build.gradle→ Java**/Gemfile→ Ruby**/Dockerfile→ Docker**/*.sql→ SQL**/webpack.config.*,**/vite.config.*,**/tsconfig.json→ Build tools
Step 2: Spawn 13 Parallel Agents
Launch ALL agents simultaneously using the Agent tool. Each agent receives:
- Its domain name and reference file path
- The detected tech stack (so it can focus on relevant patterns)
- The project root path
- Instructions to NOT read code files, only Grep/Glob for patterns
Agent definitions (spawn all 13 in a single message):
| # | Agent Name | Reference File | Focus |
|---|---|---|---|
| 1 | Database & Queries | references/database-queries.md |
N+1 queries, SELECT *, missing indexes, ORM misuse, connection pooling |
| 2 | Memory & Resources | references/memory-resources.md |
Memory leaks, unclosed resources, large allocations, string concat in loops |
| 3 | Algorithmic Complexity | references/algorithmic-complexity.md |
O(n^2) patterns, unnecessary iterations, wrong data structures for lookups |
| 4 | Concurrency & Async | references/concurrency-async.md |
Sequential awaits, blocking in async, race conditions, unbounded concurrency |
| 5 | Bundle & Dependencies | references/bundle-dependencies.md |
Heavy imports, unused deps, duplicate libs, missing lazy loading |
| 6 | Dead Code & Redundancy | references/dead-code-redundancy.md |
Unused exports, commented code, dead branches, duplicate logic |
| 7 | I/O & Network | references/io-network.md |
Sequential requests, missing batching, no dedup, missing compression |
| 8 | Rendering & UI | references/rendering-ui.md |
Re-renders, missing virtualization, layout thrashing, animation perf |
| 9 | Data Structures | references/data-structures.md |
Wrong structures, unnecessary copies, inefficient serialization |
| 10 | Error & Resilience | references/error-resilience.md |
Missing timeouts, swallowed errors, no retries, no circuit breakers |
| 11 | Caching & Memoization | references/caching-memoization.md |
Missing memoization, cache without invalidation, redundant API calls |
| 12 | Build & Compilation | references/build-compilation.md |
Dev code in prod, missing optimization flags, slow tests, Docker issues |
| 13 | Security-Performance | references/security-performance.md |
Crypto misuse, missing rate limiting, ReDoS, SQL injection vectors |
What ships with it
15 files 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.
- references/algorithmic-complexity.md 2.8 KB
- references/build-compilation.md 3.6 KB
- references/bundle-dependencies.md 2.9 KB
- references/caching-memoization.md 3.2 KB
- references/concurrency-async.md 3.0 KB
- references/config-infra.md 2.8 KB
- references/data-structures.md 3.3 KB
- references/database-queries.md 2.3 KB
- references/dead-code-redundancy.md 2.7 KB
- references/error-resilience.md 3.2 KB
- references/io-network.md 3.3 KB
- references/logging-observability.md 2.6 KB
- references/memory-resources.md 2.2 KB
- references/rendering-ui.md 3.9 KB
- references/security-performance.md 2.8 KB
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.
- 18d ago Changed · +3 lines 464b330cdd13
- 1mo ago First seen · 156 lines · 94 tokens per session scan A 32c7ad9351d0
code-optimizer is a skill published in the GitHub repository open-gsd/gsd-pi (1,326 stars, last pushed yesterday), licensed MIT. It adds 94 tokens to every session and 1,734 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
gsd-code-review
Review source files changed during a phase for bugs, security issues, and code quality problems.
gsd-review
Request cross-AI peer review of phase plans from external AI CLIs.
gsd-ns-review
quality gates | code review debug audit security eval ui.
gsd-pr-branch
Create a clean PR branch by filtering out .planning/ commits — ready for code review.
gsd-graphify
Build, query, and inspect the project knowledge graph in .planning/graphs/.
gsd-quick
Execute a quick task with GSD guarantees (atomic commits, state tracking) but skip optional agents.