Agent skill

Optimizing

by OdradekAI in OdradekAI/bundles-forge

A skill your agent uses when optimizing a bundle-plugin or single skill — improving descriptions, reducing tokens, fixing audit findings, restructuring workflows, adding skills to fill gaps, or…

Apache-2.0Auto-check passedLegal & Compliance

Install Optimizing

skills CLI
$ npx skills add OdradekAI/bundles-forge --skill optimizing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install OdradekAI/bundles-forge optimizing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/OdradekAI/bundles-forge.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/optimizing .claude/skills/optimizing && rm -rf skills-src

Use ~/.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/

Facts

Skill name
optimizing
GitHub stars
229
Token cost
~5.2k tokens
SKILL.md length
2,336 words
Files
6 (incl. references)
Skills in repo
8
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when optimizing a bundle-plugin or single skill — improving descriptions, reducing tokens, fixing audit findings, restructuring workflows, adding skills to fill gaps, or…

  • Works in 4 steps: Resolve the workspace. The workspace is… → Normalize the target by type → Create the target subdirectory if it… → …
  • Optimizing a bundle-plugin
  • SKILL.md covers Overview, Step 1: Resolve Input & Detect…, Project Optimization and Single-Skill Optimization, plus 5 more sections
  • Calls git

What it does

Optimizing is an agent skill from OdradekAI/bundles-forge. Use when optimizing a bundle-plugin or single skill — improving descriptions, reducing tokens, fixing audit findings, restructuring workflows, adding skills to fill gaps, or iterating on user feedback

Its SKILL.md is about 5.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/ab-eval-protocol.md`, `references/deprecation-guide.md` and `references/optimization-decision-trees.md`).

It sits in Legal & Compliance, covering Audit readiness. The repository describes itself as: An agentic skills framework & bundle-plugin engineering toolkit that works. The licence is Apache-2.0.

When your agent uses it

  • Optimizing a bundle-plugin
  • Single skill — improving descriptions
  • Reducing tokens
  • Fixing audit findings

Example prompts

  • “/optimizing”

Requirements

  • Pre-approved tools (allowed-tools): Bash(bundles-forge audit-skill *), Bash(bundles-forge audit-security *), Bash(bundles-forge audit-docs *), Bash(bundles-forge audit-plugin *), Bash(bundles-forge audit-workflow *), Bash(bundles-forge checklists *)

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Resolve the workspace. The workspace is $CLAUDE_PROJECT_DIR or $CURSOR_PROJECT_DIR (plugin mode), falling back to the current working…
  2. Normalize the target by type
  3. Create the target subdirectory if it does not exist.
  4. On failure (network error, 404, auth required, rate limit): tell the user what failed and suggest providing a local path or zip file…

What it can do on your machine

Read from SKILL.md and the folder at commit c1b0e10. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash(bundles-forge audit-skill *)
    • Bash(bundles-forge audit-security *)
    • Bash(bundles-forge audit-docs *)
    • Bash(bundles-forge audit-plugin *)
    • Bash(bundles-forge audit-workflow *)
    • Bash(bundles-forge checklists *)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Optimizing loads about 5.2k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 53 tokens; SKILL.md has 2,336 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~5.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~10k

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 OdradekAI/bundles-forge at commit c1b0e10, republished under its Apache-2.0 licence (© OdradekAI). 2,336 words, ~5,202 tokens.

Download SKILL.mdSave it as .claude/skills/optimizing/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
optimizing
description
Use when optimizing a bundle-plugin or single skill — improving descriptions, reducing tokens, fixing audit findings, restructuring workflows, adding skills to fill gaps, or iterating on user feedback
allowed-tools
Bash(bundles-forge audit-skill *), Bash(bundles-forge audit-security *), Bash(bundles-forge audit-docs *), Bash(bundles-forge audit-plugin *), Bash(bundles-forge audit-workflow *), Bash(bundles-forge checklists *)

Optimizing Bundle-Plugins

Overview

Orchestrate targeted improvement of a bundle-plugin project or a single skill. Unlike a full audit, optimization focuses on goals: better triggering, lower token cost, tighter workflow chains, and feedback-driven skill refinement. This skill diagnoses issues, decides on improvements, and delegates content changes to bundles-forge:authoring.

Core principle: Optimize for the agent's experience. Diagnose → decide → delegate → verify.

Skill type: Hybrid — follow the execution flow rigidly (diagnose → decide → delegate → verify), but select targets and adapt execution strategies flexibly based on audit findings and user goals.

Announce at start: "I'm using the optimizing skill to improve [this project / this skill]."

Step 1: Resolve Input & Detect Scope

The target can be a local path, a GitHub URL, or a zip file. Normalize the input to a local directory before scope detection.

Input Normalization

Edge cases & naming conventions: bundles-forge:auditing — references/input-normalization.md

This is a mandatory step — do not skip it or improvise paths. Resolve the target to a local directory before proceeding to Scope Detection.

  1. Resolve the workspace. The workspace is $CLAUDE_PROJECT_DIR or $CURSOR_PROJECT_DIR (plugin mode), falling back to the current working directory.
  2. Normalize the target by type:
    • Local path — use directly; no transformation needed.
    • GitHub URL — parse <owner> and <repo> from the URL. Shallow-clone to <workspace>/.bundles-forge/repos/<owner>__<repo>/ using --depth 1 --no-checkout, then run git checkout. If the directory already exists, append a __<YYYYMMDD> timestamp to avoid collisions. Do not clone to /tmp/, ~/, or any path outside .bundles-forge/repos/.
    • Zip/tar.gz — extract to <workspace>/.bundles-forge/repos/<archive-name>/.
  3. Create the target subdirectory if it does not exist.
  4. On failure (network error, 404, auth required, rate limit): tell the user what failed and suggest providing a local path or zip file instead. Do not silently skip or proceed with partial data.

See the canonical source for the full naming convention (version/timestamp suffixes), GitHub subdirectory URLs, and security rules.

Scope Detection

Prerequisites: Target resolved to a local path (via Input Normalization above).

After normalization, determine the scope from the resolved local path:

TargetHow to DetectMode
Project rootHas skills/ directory and package.jsonProject optimization — all 6 targets
Single skill directoryContains SKILL.md but no skills/ subdirectorySkill optimization — 3 targets + feedback iteration
Single SKILL.md filePath ends in SKILL.mdSkill optimization — 3 targets + feedback iteration

If the target is a single skill, skip to the Skill Optimization section below.


Project Optimization

Process
  1. Diagnose — run audit scripts, assess skill health, detect workflow gaps
  2. Classify & Route — classify action type, select applicable targets
  3. Apply — execute selected targets, delegate content changes to authoring
  4. Verify — re-audit to confirm improvement
Diagnostic Tools
Audit Script Baseline

Run the quality linter to identify frontmatter issues, description anti-patterns, and broken references before manual optimization:

bash
bundles-forge audit-skill <target-dir>        # markdown report
bundles-forge audit-skill --json <target-dir>  # machine-readable

The linter automates checks Q1-Q15 and X1-X3 from the skill quality ruleset. Focus manual effort on the subjective targets below.

Skill Health Assessment

Assess each skill across four qualitative dimensions: trigger confidence, execution clarity, end-to-end completeness, and degradation signals. See references/optimization-decision-trees.md for the full assessment framework and signal-to-target mapping.

Workflow Gap Detection

When findings reveal structural gaps (not just broken connections but missing capabilities), consider creating new skills via the CAPTURED action type. See references/optimization-decision-trees.md for the gap detection signals.

Routing & Classification

Route findings to targets and classify each action (FIX / DERIVED / CAPTURED) before delegating. See references/optimization-decision-trees.md for:

  • Target routing table — maps Q/W/SC findings and user signals to the 6 targets
  • Action classification — FIX (repair defect), DERIVED (enhance/specialize), CAPTURED (new skill for gap)
  • Pre-delegation checklist — classification rationale, impact analysis, scope preservation
Target 1: Skill Description Triggering

The highest-impact optimization. Descriptions are the primary mechanism for skill discovery.

Diagnosis — identify descriptions that summarize workflow, exceed 250 characters, are too narrow/broad, or fail to start with "Use when...".

Decision — draft the improved description and rationale. Use A/B eval (see below) to compare triggering accuracy before and after.

Delegation — invoke bundles-forge:authoring with a precise change spec: the old description verbatim, the new description, the rationale tied to a specific diagnosis (audit finding, health assessment dimension, or user feedback), and the action classification (FIX/DERIVED). Do not ask authoring to "improve the description" — specify the exact change.

Guiding principle: Use A/B eval when a change could produce regression effects — when improving one dimension might degrade another. Each eval scenario below defines its own skip conditions based on what kind of regression is possible.

A/B Eval for Description Changes

Follow references/ab-eval-protocol.md using the Description Triggering context. Compare trigger rate, false negatives, and false positives. Skip A/B if the change is purely additive.

If subagent dispatch is unavailable: the A/B eval protocol includes a fallback section — ask the user to choose between sequential inline evaluation (read agents/evaluator.md and follow inline) or skipping A/B in favor of a simple verification pass.

Target 2: Content Optimization
Token Budget

Canonical source: Token budgets are defined in bundles-forge:authoring (Token Efficiency section).

Diagnosis — identify skills exceeding token budgets (SKILL.md body > 500 lines, bootstrap > 200 lines), duplicated content, sections that should be in references/.

Decision — determine what to extract, merge, or cut. Map specific sections to their target location.

Delegation — invoke bundles-forge:authoring with a section-level restructuring spec: which sections to extract (source heading → target file in references/), which content to cut (quote the specific lines), and which cross-references to add. Authoring should modify only the named sections, not rewrite the entire SKILL.md.

Layer Assignment

Diagnosis — verify the three-level loading structure (metadata / SKILL.md body / references) is properly layered. Identify skills where the body contains content that belongs at a different level.

Decision — determine which sections to promote (to metadata) or demote (to references/).

Delegation — invoke bundles-forge:authoring with per-section move instructions: for each section being promoted or demoted, specify the source location, the target level, and the reason (e.g. "move lines 45-80 to references/platform-details.md because this content is only needed during platform adaptation, not on every skill load").

Target 3: Workflow Chain Integrity

Consume the workflow-report from bundles-forge:auditing (Workflow mode) to identify and fix workflow issues. If no workflow report is available, run the workflow audit first:

bash
bundles-forge audit-workflow <target-dir>                          # full workflow audit
bundles-forge audit-workflow --focus-skills skill-a,skill-b <root>   # focused on specific skills

Fix by W-check priority: See references/optimization-decision-trees.md for the full W1-W10 fix table.

After fixes — Chain A/B Eval:

Follow references/ab-eval-protocol.md using the Chain Integrity context. Use after modifying Inputs/Outputs sections, adding new skills to a chain, or when W1-W4 findings indicate integrity issues.

Target 4: Security Remediation (project only)

Fix security findings from bundles-forge:auditing Category 10.

Targets:

  • Remove unnecessary system access from hook scripts (least privilege)
  • Scope OpenCode plugin capabilities to declared needs only
  • Remove or justify any network calls in hooks/plugins
  • Ensure agent prompts include scope constraints
  • Strip encoding tricks or obfuscated content from SKILL.md files

Process: Run security scan first, then address findings by priority — critical before warnings, warnings before info:

bash
bundles-forge audit-security <target-dir>

Alternatively, invoke bundles-forge:auditing for a full audit that includes security (Category 10).

Target 5: Skill & Workflow Restructuring (project only)

Structural changes to achieve user goals: adding skills, replacing skills, reorganizing workflow chains, or converting skills to subagents. See references/restructuring-operations.md for the full step-by-step procedures (5a Adding, 5b Replacing, 5c Reorganizing, 5d Skill-to-Agent Conversion).

Target 6: Optional Component Management (project only)

Add, adjust, or migrate optional plugin components based on evolving project needs. This target handles the gap between initial scaffolding and the components a project needs as it matures.

Diagnosis — identify signals that a component is needed. See references/optimization-decision-trees.md for the full signal-to-component mapping table (userConfig, MCP, LSP, output-styles, PLUGIN_DATA, path migration).

Decision — read bundles-forge:scaffolding — references/external-integration.md for the full decision tree (CLI vs MCP, userConfig schema, PLUGIN_DATA patterns, LSP fields, output-styles format, settings.json scope).

Execution — invoke bundles-forge:scaffolding using its "Adding Optional Components" flow. Scaffolding handles file generation, manifest updates, and inspector validation.

Verification — after scaffolding completes, run bundles-forge:auditing to confirm structural integrity and security compliance (especially for new MCP servers and userConfig sensitive values).

Show full SKILL.md (1,066 more words)Show less
Target 7: Deprecation and Migration (project only)

Coordinate the deprecation, renaming, splitting, or merging of skills. This target ensures all references remain consistent across the project during structural changes.

For the full step-by-step process, see references/deprecation-guide.md.

Deprecation — mark a skill as deprecated without removing it:

  1. Add deprecated: true and superseded-by: <project>:<replacement> to the skill's frontmatter
  2. Prepend the description with a deprecation notice: "Use when... (deprecated — use <replacement> instead)"
  3. Update the bootstrap routing table to note the deprecation
  4. Update cross-references in other skills' ## Integration sections

Renaming — change a skill's name while preserving all connections:

  1. Rename the directory: skills/old-name/ → skills/new-name/
  2. Update frontmatter name field
  3. Update all cross-references (<project>:old-name → <project>:new-name) across all SKILL.md, Integration sections, and documentation
  4. Update bootstrap routing table
  5. Run bundles-forge audit-docs to catch any missed references

Splitting — divide a skill into multiple focused skills:

  1. Design the new skill boundaries (reuse bundles-forge:blueprinting scenario B)
  2. Invoke bundles-forge:scaffolding for new skill directories
  3. Invoke bundles-forge:authoring to write each new skill's content
  4. Update all references to the original skill
  5. Deprecate the original (or remove if all functionality is covered)
  6. Run bundles-forge:auditing in workflow mode to verify chain integrity

Merging — combine multiple skills into one:

  1. Design the merged skill (reuse bundles-forge:blueprinting scenario C)
  2. Invoke bundles-forge:authoring to write the merged content
  3. Deprecate the source skills
  4. Update all cross-references and routing
  5. Run bundles-forge:auditing in workflow mode

Platform cleanup — after any structural change:

  1. Remove deprecated skill references from platform manifests (Cursor plugin.json paths)
  2. Update version-bump.json if manifest paths changed
  3. Run bundles-forge:testing to verify component discovery

Single-Skill Optimization

When the target is a single skill, run only the targets that apply at skill scope. This is auto-detected — no special flags needed.

Applicable Targets
TargetApplicableWhat to Do
1. Description TriggeringFullEvaluate and improve the description's triggering accuracy
2. Content OptimizationFullCheck token budget, references extraction, layer assignment
3. Workflow Chain IntegrityPartialFix this skill's W9/W10 findings (Inputs/Outputs clarity, integration symmetry)
4. Security RemediationPartialFix security issues within this skill's content
5. Skill & Workflow RestructuringSkipProject-level concern
6. Optional Component ManagementSkipProject-level concern
7. Deprecation and MigrationSkipProject-level concern
Feedback IterationFullProcess user feedback with 3-question validation
Skill Process
  1. Read target skill — consume skill-report if available (or extract per-skill findings from audit-report)
  2. Determine goal — engineering optimization or feedback iteration?
  3. Engineering path: diagnose applicable targets (1-3, partial 4)
  4. Feedback path: run the Feedback Iteration process (below)
  5. Delegate content changes to bundles-forge:authoring
  6. Verify — run bundles-forge:auditing (skill mode) for post-change verification
Script Shortcuts
bash
bundles-forge audit-skill <skill-directory>     # quality checks on single skill

Feedback Iteration

Process user feedback about a specific skill's behavior or output quality. This is a cross-cutting concern — available in both project and skill optimization modes. Use this when a user reports that a skill triggered but produced wrong results, skipped steps, or needs better wording.

Classify the Feedback
SignalAction
"This skill triggered but produced wrong results"Feedback iteration (below)
"The steps in this skill are in the wrong order"Feedback iteration (below)
"Description format doesn't follow conventions"Use optimization targets 1-2
"Token budget exceeded across the project"Use optimization target 2 (project mode)
The Feedback Process
Receive feedback
  → Identify target skill
  → If external skill: fork with `forked-` prefix before modifying
  → Read skill, understand core goal
  → Validate each feedback item (goal alignment, necessity, side effects)
  → Present improvement plan to user
  → USER CONFIRMS ← gate
  → Copy skill to working version (<skill-name>-optimized/)
  → Delegate changes to bundles-forge:authoring on the copy
  → A/B eval: subagent A (original) vs subagent B (optimized) with same input
  → Present comparison to user
  → User adopts → replace original; User rejects → discard copy
  → Run bundles-forge:auditing for post-change verification

Validation framework — for each feedback item, ask three questions:

  1. Goal alignment: Does this serve the skill's core goal, or push it toward a different purpose?
  2. Necessity: Without this change, does the skill have an actual defect (vs. a style preference)?
  3. Side effects: Could this introduce complexity creep, scope expansion, or regression?
A/B Eval for Feedback Changes

Follow references/ab-eval-protocol.md using the Feedback Iteration context. Compare output quality and behavioral correctness. Skip if the feedback is about structural issues.

Rules:

  • Never apply feedback without user confirmation of the improvement plan
  • For external skills, always fork first (prefix with forked-, add provenance header)
  • After all changes, invoke bundles-forge:auditing for post-change verification — one audit pass only (auditing reports; optimizing decides)

Common Mistakes

MistakeFix
Optimizing everything at oncePick one target, measure, improve, verify
Adding MUST/ALWAYS/NEVER instead of explaining whyExplain the reasoning — agents respond to understanding
Splitting skills too aggressivelyOnly split when there's a genuine responsibility boundary
Ignoring token budget for bootstrapBootstrap loads every session — every word counts
Applying feedback without validationEvery item goes through the 3-question framework
Expanding skill scope during any optimizationOptimization should improve how well a skill fulfills its goal, not shift what the goal is. Verify after every change: does this skill still do the same thing?
Running all 7 targets on a single skillLet scope auto-detection handle it — targets 4-7 don't fully apply
Rewriting entire SKILL.md instead of surgical editsSpecify section-level changes in delegation. A FIX to one heading should not trigger a full rewrite — minimize diff surface to reduce regression risk
Adding third-party skills without security auditAlways run bundles-forge:auditing — see references/third-party-integration.md
Adding skills without updating Integration sectionsEvery new connection needs symmetric Calls / Called by declarations

Inputs

  • audit-report (optional) — findings from bundles-forge:auditing (full project mode). Contains per-skill breakdowns — when optimizing a single skill from a full audit, extract the relevant skill's findings from the Per-Skill Breakdown section
  • skill-report (optional) — findings from bundles-forge:auditing (skill mode). More precise input for Skill Optimization — 4-category scored report targeting a single skill
  • workflow-report (optional) — workflow-specific findings (W1-W11) from bundles-forge:auditing (workflow mode), consumed by Target 3
  • user-feedback (optional) — behavioral feedback about skill quality, triggering issues, or wrong output

Outputs

  • optimized-skill — improved SKILL.md content with better descriptions, reduced tokens, or fixed workflow references
  • eval-report (optional) — optimization record written to .bundles-forge/evals/, structured as:
    • Action type: FIX, DERIVED, or CAPTURED
    • Change summary: one sentence describing what changed and why
    • Diagnosis basis: which health dimension, audit finding, or user feedback triggered this optimization
    • Before/after comparison: A/B eval results, or verification pass outcome if A/B was skipped

Integration

Called by:

  • bundles-forge:releasing — fix quality findings during release pipeline
  • User directly — standalone optimization of any project or skill

Calls:

  • bundles-forge:authoring — all content changes (descriptions, token optimization, restructuring, third-party adaptation)
    • Artifact: optimized-skill → optimization-spec (indirect — optimizing formulates the spec, authoring receives it as targeted change instructions)
  • bundles-forge:scaffolding — Platform Coverage routing for adding new platforms; Optional Component Management target for adding MCP/LSP/userConfig/output-styles
    • Artifact: optimized-skill → project-directory (indirect — scaffolding operates on the project directory, not the optimization output)
  • bundles-forge:auditing — post-change verification (one pass, no loops)
    • Artifact: optimized-skill → project-directory (indirect — auditing targets the project containing the optimized skill)

Pairs with:

  • bundles-forge:releasing — after optimization, versions may need sync

© OdradekAI, Apache-2.0. 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 5 other files (references) in skills/optimizing of OdradekAI/bundles-forge.

  • SKILL.md
  • references/ab-eval-protocol.md
  • references/deprecation-guide.md
  • references/optimization-decision-trees.md
  • references/restructuring-operations.md
  • references/third-party-integration.md

Open the folder on GitHubat commit c1b0e10

Compare with similar skills

Optimizing 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.

Optimizing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Optimizing this skillOdradekAI/bundles-forge229—~5.2kAutomated safety check: PassApache-2.0
HIPAA Safe Harbor Coverage Auditmaziyarpanahi/openmed5.5k—~1.7kAutomated safety check: PassApache-2.0
ISO Standards Readiness EvidenceK-Dense-AI/scientific-agent-skills48k1 repos~4.6kAutomated safety check: NotesMIT
Iso42001Sushegaad/Claude-Skills-Governance-Risk-and-Compliance9391 repos~3.7kAutomated safety check: PassMIT
Fleet Triagegoogle-labs-code/jules-sdk136—~1.2kAutomated safety check: PassApache-2.0
PCI DSS Compliancewshobson/agents40k10 repos~1.9kAutomated safety check: PassMIT

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Questions about Optimizing

What does Optimizing do?

A skill your agent uses when optimizing a bundle-plugin or single skill — improving descriptions, reducing tokens, fixing audit findings, restructuring workflows, adding skills to fill gaps, or…. Optimizing is an agent skill from OdradekAI/bundles-forge.

When should I use Optimizing?

Optimizing fits situations like: optimizing a bundle-plugin; single skill — improving descriptions; reducing tokens; fixing audit findings.

How do I install Optimizing in Claude Code?

Run `npx skills add OdradekAI/bundles-forge --skill optimizing -a claude-code`. Or copy the skill folder (skills/optimizing in OdradekAI/bundles-forge) into .claude/skills/optimizing in your project. Claude Code loads it when a task matches its description.

How do I install Optimizing in Codex?

Run `npx skills add OdradekAI/bundles-forge --skill optimizing -a codex`. Or copy the skill folder (skills/optimizing in OdradekAI/bundles-forge) into .agents/skills/optimizing in your project. Codex loads it when a task matches its description.

Can I use Optimizing 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 OdradekAI/bundles-forge --skill optimizing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/optimizing, .gemini/skills/optimizing, .github/skills/optimizing and .opencode/skills/optimizing in your project.

What does Optimizing need to run?

Going by SKILL.md and its folder, Optimizing needs the command-line tools its instructions call (git). Its frontmatter pre-approves these tools: Bash(bundles-forge audit-skill *), Bash(bundles-forge audit-security *), Bash(bundles-forge audit-docs *), Bash(bundles-forge audit-plugin *), Bash(bundles-forge audit-workflow *), Bash(bundles-forge checklists *).

Does Optimizing access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Optimizing 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 Optimizing use?

Optimizing is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Optimizing use?

About 5.2k tokens (SKILL.md is roughly 21k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.1k tokens, read only when the agent opens those files.

What are the alternatives to Optimizing?

Skills that share tags, products or a category with Optimizing: HIPAA Safe Harbor Coverage Audit (maziyarpanahi/openmed, 5.5k stars), ISO Standards Readiness Evidence (K-Dense-AI/scientific-agent-skills, 48k stars), Iso42001 (Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, 939 stars) and Fleet Triage (google-labs-code/jules-sdk, 136 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Optimizing?

OdradekAI (a GitHub organization) maintains it in OdradekAI/bundles-forge, which has 229 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on April 27, 2026.

Source: OdradekAI/bundles-forge on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.