Cognee CLI Memory Commands
topoteretes/cognee
Drives cognee from the terminal with remember, recall, forget and improve memory commands, dataset and config management and database migrations.
Performance impact assessment for items with the needs-perf-review trait.
Install Perf Review
$ npx skills add jpicklyk/task-orchestrator --skill perf-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jpicklyk/task-orchestrator perf-review --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/perf-review .claude/skills/perf-review && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "perf-review" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/.claude/skills/perf-review into .claude/skills/perf-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perf-review", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/jpicklyk/task-orchestrator/tree/main/.claude/skills/perf-reviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add jpicklyk/task-orchestrator --skill perf-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jpicklyk/task-orchestrator perf-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/perf-review .agents/skills/perf-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "perf-review" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/.claude/skills/perf-review into .agents/skills/perf-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perf-review", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jpicklyk/task-orchestrator --skill perf-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jpicklyk/task-orchestrator perf-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/perf-review .cursor/skills/perf-review && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "perf-review" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/.claude/skills/perf-review into .cursor/skills/perf-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perf-review", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/jpicklyk/task-orchestrator.git --path .claude/skills/perf-review--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add jpicklyk/task-orchestrator --skill perf-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jpicklyk/task-orchestrator perf-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/perf-review .gemini/skills/perf-review && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "perf-review" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/.claude/skills/perf-review into .gemini/skills/perf-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perf-review", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install jpicklyk/task-orchestrator perf-reviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add jpicklyk/task-orchestrator --skill perf-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/perf-review .github/skills/perf-review && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "perf-review" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/.claude/skills/perf-review into .github/skills/perf-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perf-review", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jpicklyk/task-orchestrator --skill perf-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jpicklyk/task-orchestrator perf-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/perf-review .opencode/skills/perf-review && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "perf-review" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/.claude/skills/perf-review into .opencode/skills/perf-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perf-review", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
perf-review- GitHub stars
- 207
- Token cost
- ~731 tokens
- SKILL.md length
- 345 words
- Files
- 1
- Skills in repo
- 28
- Repo updated
- First seen
- Licence
- MIT
At a glance
Performance impact assessment for items with the needs-perf-review trait.
- Works in 5 steps: Hot Path Analysis → Database Query Patterns → JSON/Serialization Cost → …
- Agent Workflows work in your project
- SKILL.md covers Step 1: Hot Path Analysis, Step 2: Database Query Patterns, Step 3: JSON/Serialization Cost and Step 4: Complexity Analysis, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Perf Review is an agent skill from jpicklyk/task-orchestrator. Performance impact assessment for items with the needs-perf-review trait. Evaluates hot paths, query patterns, and measurement plans. Invoked via skillPointer when filling performance-baseline notes.
Its SKILL.md is about 730 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows. The repository describes itself as: Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what… The licence is MIT.
When your agent uses it
- Agent Workflows work in your project
Example prompts
- “/perf-review”
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit d2d362a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Perf Review loads about 731 tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 345 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from jpicklyk/task-orchestrator at commit d2d362a, republished under its MIT licence (© jpicklyk). 345 words, ~731 tokens.
Download SKILL.mdSave it as
.claude/skills/perf-review/SKILL.md (or your agent's skills folder).- name
- perf-review
- description
- Performance impact assessment for items with the needs-perf-review trait. Evaluates hot paths, query patterns, and measurement plans. Invoked via skillPointer when filling performance-baseline notes.
- user-invocable
- false
Performance Review Framework
Evaluate performance impact of changes. This project is a Kotlin MCP server with SQLite via Exposed ORM, handling tool calls synchronously per request.
Step 1: Hot Path Analysis
Identify which hot paths the change touches:
- Per-request paths — MCP tool execution (every tool call hits this). New work here adds latency to every request.
- Per-item loops — operations that iterate over items (search, overview, stalled-item detection). N+1 patterns here scale poorly.
- Startup path — server initialization, database schema creation, config loading. Affects container startup time.
- Background operations — cascade detection, dependency resolution. Runs inline, not async.
Step 2: Database Query Patterns
- N+1 queries — does the change add a query inside a loop? (e.g.,
countChildrenByRoleper child in overview). Count total queries for a typical operation. - Full table scans — any
selectAll()without filters on large tables? - Missing indexes — new filter conditions that would benefit from an index?
- Transaction scope — are transactions held open longer than necessary?
- Aggregate vs fetch-all — using
SELECT COUNT(*)withGROUP BYvs fetching all rows and counting in memory?
Step 3: JSON/Serialization Cost
- Large response payloads — does the change add fields that significantly increase response size? (e.g., adding
childCountsto every child in overview) - Repeated serialization — same object serialized multiple times in one request?
- String parsing —
PropertiesHelper.extractTraits()parses JSON on every call. Acceptable for small objects, flag if called in tight loops.
Step 4: Complexity Analysis
- What is N? — identify the scaling variable (number of items, children, notes, dependencies)
- Current complexity — O(1), O(N), O(N*M)? Where does the change sit?
- Realistic scale — what's the expected N in practice? (Most projects: <100 items, <30 children per root)
- Worst case — what happens at 1000+ items? Does it degrade gracefully or hit a wall?
Step 5: Measurement Plan
- How to verify — what should be measured before/after? (query count, response time, payload size)
- Baseline — document current performance for the affected operation
- Acceptance threshold — what's the maximum acceptable degradation?
Output
Compose the performance-baseline note with findings from each step. This note is optional (required: false) — use it when the change touches known hot paths or adds significant new work.
© jpicklyk, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .claude/skills/perf-review of jpicklyk/task-orchestrator.
Open the folder on GitHubat commit d2d362a
Compare with similar skills
Perf Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Perf Review this skilljpicklyk/task-orchestrator | 207 | — | ~731 | Automated safety check: Pass | MIT | |
| Cognee CLI Memory Commandstopoteretes/cognee | 32k | — | ~2.2k | Automated safety check: Notes | Apache-2.0 | |
| Migrate To CodexHaohao-end/openagent | 791 | 1 repos | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Openai DocsHaohao-end/openagent | 791 | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Task Listromeerez/orchid-orm | 543 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Use Gfs MCPGuepard-Corp/gfs | 158 | — | ~4k | Automated safety check: Pass | MIT |
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Remember
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When the user invokes this skill, the agent reflects on the most important lessons learned recently and suggests adding a new rule to AGENTS.md to prevent the same issue from recurring.
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Related
Categories
Questions about Perf Review
What does Perf Review do?
Performance impact assessment for items with the needs-perf-review trait. Perf Review is an agent skill from jpicklyk/task-orchestrator. Performance impact assessment for items with the needs-perf-review trait.
When should I use Perf Review?
Perf Review fits situations like: agent Workflows work in your project.
How do I install Perf Review in Claude Code?
Run `npx skills add jpicklyk/task-orchestrator --skill perf-review -a claude-code`. Or copy the skill folder (.claude/skills/perf-review in jpicklyk/task-orchestrator) into .claude/skills/perf-review in your project. Claude Code loads it when a task matches its description.
How do I install Perf Review in Codex?
Run `npx skills add jpicklyk/task-orchestrator --skill perf-review -a codex`. Or copy the skill folder (.claude/skills/perf-review in jpicklyk/task-orchestrator) into .agents/skills/perf-review in your project. Codex loads it when a task matches its description.
Can I use Perf Review in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jpicklyk/task-orchestrator --skill perf-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/perf-review, .gemini/skills/perf-review, .github/skills/perf-review and .opencode/skills/perf-review in your project.
What does Perf Review need to run?
SKILL.md names no scripts, command-line tools or credentials: Perf Review is instructions for the agent only.
Does Perf Review access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Perf Review safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Perf Review use?
Perf Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Perf Review use?
About 731 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Perf Review?
Skills that share tags, products or a category with Perf Review: Cognee CLI Memory Commands (topoteretes/cognee, 32k stars), Migrate To Codex (Haohao-end/openagent, 791 stars), Openai Docs (Haohao-end/openagent, 791 stars) and Task List (romeerez/orchid-orm, 543 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Perf Review?
jpicklyk (a GitHub user) maintains it in jpicklyk/task-orchestrator, which has 207 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 9, 2026.
Source: jpicklyk/task-orchestrator on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.