agent-toolkit

agentify-project

Make a project ready for AI agentic engineering by converging it toward a canonical agent-neutral structure — a lean AGENTS.md index with progressive disclosure, shared skills and gitignore hygiene. Re-runnable, and doubles as an audit.

attach-to-ticket

Attach pasted images, files or URLs to a fetched ticket, saved beside its ticket file and referenced from it, or fill an attachment the fetch could not download. Local only — never queries or edits the tracker.

check-ticket-implementation

Check how much of a ticket is already implemented — split it into requirement blocks, judge each against the code, and save a human-readable TICKET-STATUS report in the planning dir.

compact-docs-writer

Draft, rewrite, or refine a doc for maximum token economy without losing any rule or intent. Use for docs kept in version control and regularly re-read by agents; skip throwaway docs like plans.

compact-skill-creator

Author or refine a skill for maximum token economy without losing intent. Use when creating any new skill or editing an existing `SKILL.md`.

context-checkup

Audit what auto-loads into an agent session's context window and suggest lean, reversible fixes to cut startup tokens.

create-implementation-plan

Turn a refined requirements document into a structured implementation PLAN.md a fresh session can execute. Planning only — decides the "how", not the "what". Invoke manually only.

Testing & QA Featured

create-manual-test-instructions

Turn a ticket or requirements document into a concise QA manual-test file a non-author can follow. Invoke manually only.

execute-plan-tasks

Execute one task from a plan's task breakdown, verify it, tick it off, and hand back for review before the next one.

explain-in-simple-language

Explain code, a decision, a recap, or a question to the user in simple language that a fluent but often non-native developer who did not see what the agent saw understands on the first read. Use when explaining or asking the user anything, or when the user asks for simpler words or says they did not understand. Changes the wording only, never the content.

Code & Development Solid

fetch-pr-review

Fetch all reviewer comments from a pull request URL (GitHub, Azure DevOps, …) and save them as a self-contained markdown PR-REVIEW file in the task's planning directory. Fetch only — no fixing or replying.

Data & Documents Solid

fetch-ticket

Fetch one or more tickets/issues from their tracker (Azure DevOps, Jira, GitHub, …) and save each as a self-contained markdown ticket file. Fetch only — no analysis or planning.

Code & Development Featured

Show all 28 bundled skills

fresh-eyes-review

Fresh-eyes review of a changeset by a fresh-context agent — catches regressions and correctness issues the authoring context reads past.

grill-me

Interview the user relentlessly about a plan, design, or idea until reaching shared understanding, resolving each branch of the decision tree. Use when the user wants to stress-test a plan, validate an idea, get grilled on their design, or says "grill me".

handover

Use when handing finished work over to code review — writing a PR description or packaging a change for review by a human, an agent, or both.

maintainer-review

Review someone else's pull request as the maintainer deciding whether it merges — every prior comment walked, every claim verified, and nothing posted without your go-ahead.

memory-doctor

Audit the current project's agent-memory and, block by block, relocate each entry into a user-controlled home (project doc/skill/rule or user-level skill/rule) or archive it — draining memory so nothing uncontrolled accumulates in the agent's context.

prepare-prompt

Prepare a prompt that hands this session's work to a fresh agent session — to continue it, check it, or pick up what was left open. Use when asked for a prompt or brief for the next session.

Code & Development Solid

refine-pr-review

Triage a fetched PR review with the user, comment by comment, drafting each reply and producing a REQUIREMENTS file for the accepted code changes. Takes the PR-REVIEW file produced by fetch-pr-review. Invoke manually only.

refine-ticket

Refine a development ticket — or brainstorm a raw idea — into a validated, self-contained REQUIREMENTS document — the "what", verified against the codebase. Invoke manually only.

review-code-assistant

Assist a human reviewing a pull request or branch locally — diff a source branch against its target (auto-detected or from a PR link) and return concise, human-voice review comments with file and line locations. Read-only, never posts.

Code & Development Featured

review-ticket

Triage a ticket or ticket set before work starts — compare it against the codebase and save a review covering verdict, feature walkthrough, and only the high-cost questions worth raising.

run-nx-checks

Run nx format, lint, test, and build on affected or specified projects, then fix unambiguous failures

self-improve

Capture durable user feedback into the governing skill/doc, or propose creating a new skill when no suitable one exists, so future sessions don't repeat the mistake. Use when the user rejects, reverts, or overrides the agent's output or approach on something a skill/doc covers or should cover, and when manually invoked to improve or create guidance.

Code & Development Featured

self-review

Self-review a changeset until merge-ready — a fresh-context reviewer checks it as a maintainer would, the author answers every finding, and a compact report for the PR proves the review happened.

split-plan-tasks

Split a plan into small, individually reviewable tasks grouped into PR-sized batches, appended as a task section at the end of the plan file.

use-conversational-language

Voice rules for text published under a person's name and read as if a person typed it, such as chat replies, PR comments and descriptions, commit messages, review replies, and code comments. Defines the wording only, never the content.

verify-understanding

Verify the engineer is ready to implement a feature — a teach-back conversation over a .TICKET-REVIEW.md where they explain the feature in their own words and the agent probes and corrects.