DeepTutor CLI
HKUDS/DeepTutor
Teaches the agent to set up and run DeepTutor from the command line: chat and capabilities, knowledge bases, partners, memory, sessions, notebooks and the server or Web app.
Evaluate one existing package or bounded package family from recorded evaluator evidence and a capability profile, then propose retain, simplify, strengthen, retire, or inconclusive without editing.
Install Package Optimizer
$ npx skills add Mathews-Tom/armory --skill package-optimizer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Mathews-Tom/armory package-optimizer --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/Mathews-Tom/armory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/package-optimizer .claude/skills/package-optimizer && 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 "package-optimizer" agent skill from https://github.com/Mathews-Tom/armory/tree/main/skills/package-optimizer into .claude/skills/package-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "package-optimizer", 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/Mathews-Tom/armory/tree/main/skills/package-optimizerType 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 Mathews-Tom/armory --skill package-optimizer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Mathews-Tom/armory package-optimizer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mathews-Tom/armory.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/package-optimizer .agents/skills/package-optimizer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "package-optimizer" agent skill from https://github.com/Mathews-Tom/armory/tree/main/skills/package-optimizer into .agents/skills/package-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "package-optimizer", 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 Mathews-Tom/armory --skill package-optimizer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Mathews-Tom/armory package-optimizer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mathews-Tom/armory.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/package-optimizer .cursor/skills/package-optimizer && 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 "package-optimizer" agent skill from https://github.com/Mathews-Tom/armory/tree/main/skills/package-optimizer into .cursor/skills/package-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "package-optimizer", 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/Mathews-Tom/armory.git --path skills/package-optimizer--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 Mathews-Tom/armory --skill package-optimizer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Mathews-Tom/armory package-optimizer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mathews-Tom/armory.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/package-optimizer .gemini/skills/package-optimizer && 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 "package-optimizer" agent skill from https://github.com/Mathews-Tom/armory/tree/main/skills/package-optimizer into .gemini/skills/package-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "package-optimizer", 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 Mathews-Tom/armory package-optimizerInstalls 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 Mathews-Tom/armory --skill package-optimizer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Mathews-Tom/armory.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/package-optimizer .github/skills/package-optimizer && 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 "package-optimizer" agent skill from https://github.com/Mathews-Tom/armory/tree/main/skills/package-optimizer into .github/skills/package-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "package-optimizer", 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 Mathews-Tom/armory --skill package-optimizer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Mathews-Tom/armory package-optimizer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mathews-Tom/armory.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/package-optimizer .opencode/skills/package-optimizer && 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 "package-optimizer" agent skill from https://github.com/Mathews-Tom/armory/tree/main/skills/package-optimizer into .opencode/skills/package-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "package-optimizer", 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
package-optimizer- GitHub stars
- 328
- Token cost
- ~1.4k tokens
- SKILL.md length
- 529 words
- Files
- 2
- Skills in repo
- 80
- Repo updated
- First seen
- Licence
- MIT
At a glance
Evaluate one existing package or bounded package family from recorded evaluator evidence and a capability profile, then propose retain, simplify, strengthen, retire, or inconclusive without editing.
- Works in 4 steps: Package scope — one type/name package or… → Current evidence — static conformance… → Capability profile —… → …
- Optimizing a skill
- SKILL.md covers Scope, Required inputs, Evidence validity and Procedure, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Package Optimizer is an agent skill from Mathews-Tom/armory. Evaluate one existing package or bounded package family from recorded evaluator evidence and a capability profile, then propose retain, simplify, strengthen, retire, or inconclusive without editing. Use when optimizing a skill, agent, hook, rule, command, utility, or preset; evaluating whether package detail is justified; reviewing a model-refresh impact; or preparing an approval-gated package improvement. Refuses missing, stale, or incomparable evidence and never edits without explicit approval. Not for scoring…
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `evals/cases.yaml`).
It sits in Education, covering Quizzes and assessments. The repository describes itself as: Curated, production-grade skills for AI coding agents. Battle-tested workflows for developers who use AI seriously. The licence is MIT.
When your agent uses it
- Optimizing a skill
- Evaluating whether package detail is justified
- Reviewing a model-refresh impact
- Preparing an approval-gated package improvement
Example prompts
- “/package-optimizer”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Package scope — one type/name package or an explicitly bounded family.
- Current evidence — static conformance and relevant eval-case result or a
- Capability profile — model/client/tool-surface identity when behavioral
- Decision question — what behavior should be retained, simplified, or
What it can do on your machine
Read from SKILL.md and the folder at commit 4594fb7. 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
Package Optimizer loads about 1.4k tokens when it runs. Until then it costs about 152 tokens; SKILL.md has 529 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 Mathews-Tom/armory at commit 4594fb7, republished under its MIT licence (© Mathews-Tom). 529 words, ~1,378 tokens.
Download SKILL.mdSave it as
.claude/skills/package-optimizer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- package-optimizer
- description
- Evaluate one existing package or bounded package family from recorded evaluator evidence and a capability profile, then propose retain, simplify, strengthen, retire, or inconclusive without editing. Use when optimizing a skill, agent, hook, rule, command, utility, or preset; evaluating whether package detail is justified; reviewing a model-refresh impact; or preparing an approval-gated package improvement. Refuses missing, stale, or incomparable evidence and never edits without explicit approval. Not for scoring static package conformance or rubric dimensions; use package-evaluator.
- metadata.version
- 1.0.0
- metadata.category
- development
- metadata.phase
- review
- metadata.tags
- package, optimization, evaluation, evidence, approval
- metadata.difficulty
- advanced
Package Optimizer
Turn existing package evidence into one bounded, reviewable proposal. The optimizer is proposal-only: it never edits a package, changes a profile, or starts a benchmark run.
Scope
| Situation | Action |
|---|---|
| One package has current evaluator evidence | Propose one disposition. |
| A bounded family shares the same evidence/profile | Propose one family plan with a per-package row. |
| Evidence is missing, stale, structurally invalid, or from another profile | Return inconclusive; name the unresolved package decision and request the smallest recertification needed. |
| User asks to apply a proposal | Require explicit approval, preserve before artifacts, then hand the edit to the normal package workflow. |
| User asks for a broad benchmark before identifying a package decision | Refuse the expansion; identify the package decision first. |
Required inputs
- Package scope — one
type/namepackage or an explicitly bounded family. - Current evidence — static conformance and relevant eval-case result or a recorded behavioral result. Cite exact commands, artifacts, or case IDs.
- Capability profile — model/client/tool-surface identity when behavioral evidence depends on one. Structural-only evidence is labelled as such.
- Decision question — what behavior should be retained, simplified, or strengthened.
Do not infer effectiveness from package length, heading count, or static score.
Evidence validity
Reject evidence when any condition holds:
- package path, version, or evaluator case differs from the proposed scope;
- a behavioral result has no model/client/tool-surface identity;
- a profile is older than a recorded package change or cannot be compared to the requested profile;
- the evidence omits a failure, safety outcome, or relevant evaluator result;
- an M4 recertification report pools model targets or lacks complete cells.
A rejection uses the single output format below with Disposition: inconclusive,
Proposed change: none, and Approval required: yes. Its Unresolved package decision must name the package scope and decision question. A recertification
request repeats that exact field; do not request a benchmark without it.
Show full SKILL.md (228 more words)Show less
Procedure
- Resolve the package scope and read its definition, evaluator cases, and current conformance output.
- State the decision question and evidence class:
structural,behavioral, orprofile-scoped behavioral. - Verify evidence validity. Stop with
inconclusiveon any invalid input. - Select exactly one disposition:
retain— evidence supports the current contract.simplify— evidence identifies redundant detail and the retained contract/evaluator proves the smaller scope.strengthen— a documented failure requires a concrete contract addition.retire— explicit deprecation or replacement evidence supports removal.inconclusive— evidence cannot support a safe change.
- Produce a proposal. For non-
retaindispositions, name exact sections or files to change and the evaluator behavior that must remain true. - Stop. Do not edit. Require the user to explicitly approve the proposal.
Approval handoff
An approval must name the package, disposition, and proposal ID. The downstream applying workflow—not this skill—must:
- Save the original package artifact and evaluator evidence.
- Apply only the approved package/family change.
- Run static conformance and relevant eval cases.
- Record before/after artifacts, verification output, profile identity, and any regression.
- Revert the bounded package change on regression. Do not broaden the scope.
Output format
## Package Optimization Proposal
Scope: <type/name or bounded family>
Decision question: <question>
Evidence class: <structural | behavioral | profile-scoped behavioral>
Evidence:
- <command/artifact/case and observed result>
Capability profile: <identity | not applicable>
Disposition: <retain | simplify | strengthen | retire | inconclusive>
Rationale: <evidence-backed explanation>
Unresolved package decision: <scope + decision question | not applicable>
Proposal ID: <stable scope + evidence identifier>
Proposed change: <none | exact files/sections and intended behavior>
Preservation check: <existing evaluator/eval case>
Approval required: yes
Smallest next action: <concrete action>Guardrails
- Never edit without explicit approval.
- Never optimize all packages at once.
- Never turn missing evidence into a simplification recommendation.
- Never claim token, cost, or quality improvement without recorded evidence.
- Prefer
retainorinconclusiveover speculative change.
© Mathews-Tom, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in skills/package-optimizer of Mathews-Tom/armory.
- SKILL.md
- evals/cases.yaml
Open the folder on GitHubat commit 4594fb7
Compare with similar skills
Package Optimizer 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 |
|---|---|---|---|---|---|---|
| Package Optimizer this skillMathews-Tom/armory | 328 | — | ~1.4k | Automated safety check: Pass | MIT | |
| DeepTutor CLIHKUDS/DeepTutor | 41k | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| AI Engineering Placement Quizrohitg00/ai-engineering-from-scratch | 66k | — | ~2k | Automated safety check: Pass | MIT | |
| Codebase to Coursezarazhangrui/codebase-to-course | 5.7k | — | ~4.4k | Automated safety check: Pass | None | |
| AI Engineering Phase Quizrohitg00/ai-engineering-from-scratch | 66k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Scholar EvaluationK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~2.9k | Automated safety check: Notes | MIT |
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Categories
Questions about Package Optimizer
What does Package Optimizer do?
Evaluate one existing package or bounded package family from recorded evaluator evidence and a capability profile, then propose retain, simplify, strengthen, retire, or inconclusive without editing. Package Optimizer is an agent skill from Mathews-Tom/armory. Evaluate one existing package or bounded package family from recorded evaluator evidence and a capability profile, then propose retain, simplify, strengthen, retire, or inconclusive without editing.
When should I use Package Optimizer?
Package Optimizer fits situations like: optimizing a skill; evaluating whether package detail is justified; reviewing a model-refresh impact; preparing an approval-gated package improvement.
How do I install Package Optimizer in Claude Code?
Run `npx skills add Mathews-Tom/armory --skill package-optimizer -a claude-code`. Or copy the skill folder (skills/package-optimizer in Mathews-Tom/armory) into .claude/skills/package-optimizer in your project. Claude Code loads it when a task matches its description.
How do I install Package Optimizer in Codex?
Run `npx skills add Mathews-Tom/armory --skill package-optimizer -a codex`. Or copy the skill folder (skills/package-optimizer in Mathews-Tom/armory) into .agents/skills/package-optimizer in your project. Codex loads it when a task matches its description.
Can I use Package Optimizer 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 Mathews-Tom/armory --skill package-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/package-optimizer, .gemini/skills/package-optimizer, .github/skills/package-optimizer and .opencode/skills/package-optimizer in your project.
What does Package Optimizer need to run?
SKILL.md names no scripts, command-line tools or credentials: Package Optimizer is instructions for the agent only.
Does Package Optimizer 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 Package Optimizer 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 Package Optimizer use?
Package Optimizer 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 Package Optimizer use?
About 1.4k tokens (SKILL.md is roughly 5.5k 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 Package Optimizer?
Skills that share tags, products or a category with Package Optimizer: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), AI Engineering Placement Quiz (rohitg00/ai-engineering-from-scratch, 66k stars), Codebase to Course (zarazhangrui/codebase-to-course, 5.7k stars) and AI Engineering Phase Quiz (rohitg00/ai-engineering-from-scratch, 66k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Package Optimizer?
Mathews-Tom (a GitHub user) maintains it in Mathews-Tom/armory, which has 328 GitHub stars. The repository holds 80 skills in this directory. The repository was last updated on October 6, 2026.
Source: Mathews-Tom/armory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.