Deployment Failure Forensics
Professional DevOps diagnostics for AI agents to solve failed deployments, Docker crashes, and CI/CD pipeline errors.
Ship agent workflows in 30 seconds. Browse 1,500+ expert-built and security scanned skills. Browse skills
THE AGENSI STORE
87 skills found
Professional DevOps diagnostics for AI agents to solve failed deployments, Docker crashes, and CI/CD pipeline errors.
Lint the function-calling tool definitions your agent exposes. Flags tools with no description, parameters missing a description or a type, overlapping or near-duplicate tools, too many tools for reliable selection, an unsafe tool exposed without a guard, required parameters missing from the schema, and free-form parameters that should be bounded with an enum. Cleaner tool schemas mean an agent that picks the right tool.
Scaffold and audit secure MCP servers with input schemas, confirmation gates, and safety-first tool definitions.
Transform fragile AI prototypes into resilient, enterprise-ready production agents with professional hardening tools.
Generate source-safe repository audits and repair handoff bundles without mutating your code.
Turns Claude into a senior WordPress launch reviewer that audits a site, theme, or plugin against the entire pre-launch standard across 7 weighted domains and returns one objective go/no-go decision with a scored blocker list.
A senior WordPress theme architect skill that migrates classic PHP themes to FSE block themes — extracting business logic into a companion plugin during conversion — and delivers both a phased reversible plan and the actual converted files.
Run a buyer-readiness check before publishing an AI agent skill package.
A professional technical editor's review for your docs. Catches missing context, unclear writing, and unverifiable claims in READMEs, API docs, and changelogs before they ship — with a PASS/REVISE verdict and a prioritized fix list.
Write and review the docs AI agents actually read — AGENTS.md for your repo and llms.txt for your site. Drafts them from scratch or audits existing ones for completeness, clarity, and wasted context, with a PASS or REVISE verdict.
Design and write the eval suite for your LLM-powered feature — the metrics that match your failure modes, a golden dataset plan with starter cases, anchored rubrics, LLM-as-judge prompts with the known bias mitigations, and pass/fail gates wired for CI.
Generate consistent API reference docs from your code, OpenAPI spec, or route handlers — per-endpoint parameters, real request and response examples, error codes, auth, and copy-pasteable curl, written for the developer calling the API.
Generate a complete, reader-ready README from your code and project details — not a template dump. It leads with what the project is and why, gives a quickstart that actually runs, and includes only the sections that apply.
Turn your diffs and commit history into commit messages, PR descriptions, and release notes that reviewers and users actually read. One skill, three jobs — conventional-commit compliant, reviewer-ready, and written in plain language.
Turn timeline fragments, Slack logs, and pager history into a complete blameless postmortem — impact summary, clean timeline, contributing factors instead of a scapegoat, action items with owners and due dates, and lessons that survive the week.
Adversarially audit your agent hooks before you trust them. Catches command injection, secret leakage, over-broad matchers, destructive actions, and blocking-logic mistakes in pre/post-tool-use, prompt, and stop hooks — with a PASS or REVISE verdict and severity-ranked fixes.
Scan your OpenClaw config for the settings that quietly hand your agent too much power: unrestricted exec, open inbound DMs, secrets committed in config, the deny-write bypass, sandbox turned off, dangerous Docker binds, and elevated tools. Read-only, plain-English findings, grounded in the OpenClaw docs.
Write the delegation brief that lets a background or async agent succeed unattended — precise goal, hard constraints, testable acceptance criteria, a verification plan, and stop-and-escalate rules. Turns "go fix the flaky tests" into a spec an agent can actually execute.
Draft the AI documentation the EU AI Act expects — model cards, AI-use disclosures, transparency notices, risk-tier worksheets, and technical-doc skeletons. Counsel-ready drafts from a regulated-industry documentation professional, with templates included.
Red-team your own AI agent for prompt-injection and tool-misuse vulnerabilities before it ships — then fix them. Maps your attack surface, generates a defensive test plan with the safe behavior expected for each case, and gives a prioritized mitigations list. Defensive use only.
Model what your LLM app or agent will cost, find where the money goes, and get a plan to cut it. Per-request and monthly projections, ranked cost drivers, an optimization plan with estimated savings, and unit economics against your pricing — with the arithmetic shown.
Verify AI-generated code for scope drift, false completions, and missing tests.
Generates a complete, polished README.md by scanning your actual project structure, dependencies, and code.
Transform raw skill documentation into high-conversion, readable marketplace listings without losing LLM context.