Agent Skills Library
Reusable specialist skills, prompts, and automation workflows for several coding-agent environments.
Per-dimension scores and reasoning
The release workflow uses read-only repository permissions, exact-commit binding, disabled persisted checkout credentials, pinned tools, a preview stage, and SHA-bound human publication gates. It creates the temporary token configuration with mode 0600 and removes it unconditionally. TODO tests also cover deletion confirmation, locking, atomic writes, backups, and an opt-in heartbeat. Deductions apply because these strong controls are evidenced mainly for the ten-package release process and one TODO utility, not for every API, scraper, updater, or CRM-writing skill in the collection. Repository-level documentation gives only limited detail about per-skill data destinations, retention, and external effects. Author, repository, paths, and commit provenance are explicit, but the publisher is unverified and the referenced AgentVerus scan results are not included as independent evidence.
The documented layout, platform positioning, and release batch are broadly consistent with the workflow. Release tests cover manifest drift, duplicate keys, paths, versions, gates, and secret printing, while TODO and Munger contract tests exercise substantial error and boundary behavior. The release chain pins Python, Node, PyYAML, and ClawHub versions. Deductions apply because no execution results are supplied, the elegant-reports workflow shows npm ci/npm test without the lockfile or test contents, and dependency availability, retry behavior, and user-facing failure messages are not demonstrated individually for most skills.
The source clearly separates universal skills, instruction-only prompts, OpenClaw-specific material, and Codex-specific material, with installation guidance for OpenClaw, Claude Code, Codex, and manual use. The Munger contract demonstrates precise activation, bounded history access, and scheduling boundaries, while the release workflow is restricted to a fixed ten-package set. Deductions apply because similarly precise boundaries are not evidenced for most skills, the underlying matrix for the 79% portability claim is absent, and repository-level documentation does not enumerate each skill's API, browser, CLI, credential, or operating-environment requirements.
The repository has clear skills/prompts/clawdbot/codex organization, structural examples, generated catalogs, and substantial multi-platform installation notes. The full MIT text agrees with the license metadata and merits full license credit. Versioned release commands and changelog summaries give ten packages stable identities, and the Clawdbot-to-OpenClaw rename is explained. Deductions apply for the lack of a complete FAQ, centralized known-limitations section, and repository-wide changelog. Examples are largely installation-oriented, and maintenance responsibility is implied by the author, contribution route, and release owner without a support policy, response commitment, deprecation cadence, or long-term maintenance statement.
The catalog addresses concrete workflows across analytics, documents, planning, CRM, advertising, reporting, and orchestration. Its classifications, short descriptions, and copyable installation commands make the collection practically approachable, while distinguishing structured skills from pure prompts aids selection. Deductions apply because the evidence contains few representative outputs, end-to-end usage cases, or comparative quality results for most skills. It also does not quantify time, token, API-quota, cloud-service, or maintenance costs; only isolated release notes mention quota or credit confirmation, so cost-benefit support remains thin.
Release paths, versions, owner, commits, and commands are traceable to the workflow. Separate test sources corroborate the release safety contract, TODO state behavior, and Munger evidence boundaries, including explicit separation of observation, inference, evidence, counterevidence, and confidence. Deductions apply because the supplied material omits the principal scripts, most SKILL.md files, the compatibility matrix, dependency lockfiles, and scanner reports, preventing repository-wide claim-by-claim verification. The 79% portability figure and claim that every skill is scanned therefore remain primarily project assertions.
- Do not treat the README's AgentVerus badge or claim that every skill is scanned as a verified security result in this assessment; the scan reports were not supplied.
- Before installation, inspect each selected SKILL.md, supporting script, dependency lockfile, credential scope, and network data destination, especially for auto-update, gallery scraping, CRM, advertising, and document-upload skills.
- The release controls cover a fixed ten-package ClawHub batch and should not be generalized to every other skill's confirmation, pinning, secret handling, or rollback behavior.
- Validate external writes and paid operations in read-only, preview, or sandbox modes first, and establish resource-specific confirmation and recovery plans for systems such as Jira, Salesforce, Zendesk, Google Ads, and Nudocs.
What does this agent do, and when should you use it?
Agent Skills is a collection of extensions for OpenClaw, Claude Code, Codex, and other LLM-based coding assistants rather than a single executable agent. Its four main areas are skills, prompts, OpenClaw-specific packages under clawdbot, and Codex-specific packages under codex. Skills may contain scripts, templates, API integrations, and structured workflows, while prompts are instruction-only packages without external dependencies. The catalog covers Jira, GA4, Google Ads, Google Search Console, Gong, Salesforce, Zendesk, document processing, research loops, planning, and multi-agent orchestration. Users install selected directories into the host assistant and remain responsible for any API credentials, CLIs, or services required by those selections. It is a good fit for teams assembling a tailored capability set, but not for adopters seeking one hosted service, uniform runtime, or turnkey agent.
Each package uses SKILL.md as its instruction entry point and may add scripts, templates, or other supporting files. Named integrations can read GA4 Data API reports, Google Search Console properties and analytics, Gong calls and transcripts, Jira work, Salesforce CRM data through the sf CLI, and Zendesk tickets or users; some also create or update records and workflows. planner produces structured plans for task-orchestrator, while task-orchestrator performs dependency analysis, parallel tmux/Codex execution, and heartbeat monitoring; parallel-task coordinates plan files and concurrent subagents. Other packages generate Nordic-style PDF reports, guide Remotion video work in React, research the last 30 days across Reddit, X, and the web, or apply frontend, writing, and senior-engineering guidance. Repository utilities include scripts/update-readme.sh for generating the catalog and scripts/validate-skills.sh for checking SKILL.md structure. There is no repository-wide execution command or common output format: behavior, permissions, inputs, and artifacts depend on the chosen package and its host.
- A Codex CLI or Claude Code user wants to add selected Jira, planning, engineering-review, or coding workflows without adopting a new hosted agent.
- A marketing analytics team wants an assistant to query GA4, Google Ads, or Google Search Console and can provision the relevant service access.
- A sales or support operations team needs focused workflows around Gong, Salesforce, or Zendesk data.
- An engineering team running a complex project wants to combine planner, parallel-task, and task-orchestrator for decomposition and coordinated execution.
- An OpenClaw operator needs platform-specific capabilities such as persistent TODOs, a knowledge graph, skill synchronization, release checks, or daily updates.
- A contributor wants a documented SKILL.md package layout with optional scripts and templates plus repository validation and catalog-generation utilities.
What are this agent's strengths and limitations?
- It combines operational skills, instruction-only prompts, and clearly separated OpenClaw- and Codex-specific packages in one catalog.
- The library targets concrete systems including Jira, GA4, Google Ads, GSC, Gong, Salesforce, and Zendesk instead of offering only generic prompt templates.
- planner, parallel-task, and task-orchestrator can be combined for structured planning, dependency analysis, and parallel execution.
- A defined SKILL.md layout, validation script, and README-generation script support consistent contribution and maintenance.
- The repository states that every skill is scanned by AgentVerus, with current results published for prompt injection, data exfiltration, and hidden-threat checks.
- This is not a uniform application or runtime; every selected skill may have different inputs, outputs, credentials, dependencies, and error behavior.
- Compatibility is not complete: the README reports 79% cross-platform coverage and separately identifies OpenClaw-only and Codex-specific packages.
- Several business integrations require external APIs, account permissions, or dedicated CLIs, with no repository-wide credential setup.
- Copy- or symlink-based installation leaves version pinning, updates, and host configuration to the adopter.
- The source does not provide one test command, first successful invocation, or reliability guarantee covering the entire collection.
How do you install or deploy this agent?
Clone the repository:
git clone https://github.com/jdrhyne/agent-skills.git ~/agent-skillsFor Claude Code, copy or link an individual skill:
cp -r skills/elegant-reports ~/.claude/skills/
ln -s $(pwd)/skills/planner ~/.claude/skills/For Codex CLI, copy the packages you need:
cp -r codex/codex ~/.codex/skills/
cp -r codex/gemini ~/.codex/skills/
cp -r codex/command-creator ~/.codex/skills/
cp -r skills/jira ~/.codex/skills/
cp -r prompts/humanizer ~/.codex/skills/Alternatively, link the repository:
ln -s $(pwd) ~/.codex/agent-skillsThen add paths to ~/.codex/config.toml:
[skills]
paths = ["~/.codex/skills/codex",
"~/.codex/skills/gemini",
"~/.codex/skills/jira"
]
OpenClaw users can add selected directories under skills.paths. Manual installation consists of copying the relevant SKILL.md and its supporting files. The repository does not document one runtime version or credential checklist for the entire collection; credentials and CLI requirements for integrations such as GA4, Jira, Salesforce, or Zendesk must be established per skill.
How do you use this agent?
Choose a package whose description matches the task, install it in the host's skill path, and ask the host assistant for an operation covered by that package. With jira installed, for example, the documented scope includes reading, searching, drafting, creating, or updating Jira work. With planner installed, request a structured multi-task plan that task-orchestrator can consume; with humanizer installed, provide text to revise for signs of AI-generated writing. Instruction-only prompts generally need only SKILL.md, while operational skills may also depend on bundled scripts, templates, an external API, or a local CLI. The source provides no single first-run invocation, shared permission model, or repository-wide failure-handling procedure, so those details must come from the selected skill and host platform.
How does this agent compare with similar options?
Compared with the companion lobster-workflows repository, Agent Skills emphasizes instructions and capabilities interpreted by an agent, while lobster-workflows is presented as deterministic automation built around typed pipelines, approval gates, state tracking, and repeatable execution. Within this repository, Skills can include scripts, templates, multi-step workflows, and external integrations; Prompts contain guidance text only.