smithery.ai

implementing-tasks

Implements tasks from .plans/ directories by following implementation guidance, writing code and tests, and updating task status. Use when task file is in implementation/ directory and requires code implementation with comprehensive testing. Launches research agents when stuck.

First seen Apr 15, 2026

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 6,544 B
  • docs SUMMARY.md 304 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Implementation

Given task file path .plans/<project>/implementation/NNN-task.md:

Process

Load Critical Patterns (if exists)

Before starting implementation, check for .plans/<project>/critical-patterns.md:

  • If exists, read and internalize all patterns
  • Apply matching patterns during implementation
  • Violations will be flagged as CRITICAL in review

Use TodoWrite to track implementation progress:

☐ Read task file (LLM Prompt, Working Result, Validation)
☐ [LLM Prompt step 1]
☐ [LLM Prompt step 2]
...
☐ Write tests for new functionality
☐ Run full test suite
☐ Mark validation checkboxes
☐ Update status to READY_FOR_TESTING

Convert each step from the task's LLM Prompt into a todo. Mark completed as you progress.

  1. Read task file - LLM Prompt, Working Result, Validation, Files
  2. Follow LLM Prompt step-by-step, write code + tests, run full suite
  3. Update task status using Edit tool:

- For initial implementation: Status: READYFORTESTING - For revision after rejection: Status: READYFORREVIEW (skip testing, go back to review)

  1. Append implementation notes using Edit tool (add to end of task file):

``markdown implementation: - Followed LLM Prompt steps 1-N - Implemented [key functionality] - Added [N] tests: all passing - Full test suite: [M]/[M] passing - Working Result verified: ✓ [description] - Files: [list with brief descriptions] ``

  1. Mark validation checkboxes: [ ][x] using Edit tool
  2. Report completion

Stuck Handling

When blocked during implementation:

1. Mark Task as Stuck

  • Update status using Edit tool:

- Find: Status: [current status] - Replace: Status: STUCK

  • Append notes using Edit tool (add to end of task file):

``markdown implementation: - Attempted [what tried] - BLOCKED: [specific issue] - Launching research agents to investigate... ``

2. Launch Research Agents

Launch 2-3 researcher agents in parallel, each in a mode matching the blocker:

  • survey: new technology or approach, best practices, comparisons
  • deep-dive: specific error, issue, or implementation examples
  • official-docs: API integration, library or framework specifics

Example:

Task(description: "Survey [technology]", prompt: "Mode: survey. How to [solve blocker]?", subagent_type: "experimental:research:researcher")
Task(description: "Official docs for [feature]", prompt: "Mode: official-docs. [library] documentation for [feature]", subagent_type: "experimental:research:researcher")

3. Synthesize Findings

Use research-synthesis skill (from essentials) to:

  • Consolidate findings from all agents
  • Identify concrete path forward
  • Extract actionable implementation guidance

Update task file with research findings using Edit tool (add to end of task file):

**research findings:**
- [Agent 1]: [key insights]
- [Agent 2]: [key insights]
- [Agent 3]: [key insights]

**resolution:**
[Concrete path forward based on research]

4. Continue or Escalate

If unblocked:

  • Update status back to IN_PROGRESS
  • Capture the learning (auto-invoked):

``` Task( description: "Capture learning from blocker resolution", prompt: "Extract the learning from this resolved blocker.

Problem context: - STUCK notes: [from task file] - Research findings: [from task file]

Resolution: - What worked: [resolution notes] - Task: [task file path]

Save under: .plans/<project>/learnings/", subagent_type: "experimental:capture:knowledge-capturer" ) ```

  • Resume implementation following research guidance
  • Complete normally as per main Process section

If still stuck after research:

  • Keep status as STUCK
  • Append escalation notes using Edit tool (add to end of task file):

``markdown escalation: - Research completed but blocker remains - Reason: [why research didn't unblock] - Need: [what's needed - human decision, missing requirement, etc.] ``

  • Then STOP and report blocker with full context.

Rejection Handling

If task moved back from review (check for review: notes in task file):

  1. Read review notes for blocking issues
  2. Fix all CRITICAL and HIGH issues
  3. Update status to READYFORREVIEW (go back to review, skip testing)
  4. Append revision notes:

`` implementation (revision): - Fixed [issue 1] - Fixed [issue 2] - Re-ran tests: [M]/[M] passing ``

Test Fix Handling

If task moved back from testing (check for testing: notes with NEEDS_FIX):

  1. Read testing notes for failures
  2. Fix the failing tests or code
  3. Update status to READYFORTESTING (go back to testing)
  4. Append fix notes:

`` implementation (test fix): - Fixed [test issue] - Re-ran tests: [M]/[M] passing ``

Completion

When implementation is complete:

  • Initial implementation: Status = READYFORTESTING
  • After review rejection: Status = READYFORREVIEW
  • After test failure: Status = READYFORTESTING

Collect Implementation Metadata

Before setting final status, collect metadata for review triage:

**implementation_metadata:**
- files_changed: [count from git diff --stat]
- lines_changed: [insertions + deletions from git diff --stat]
- was_stuck: [true/false - was task ever marked STUCK?]
- research_agents_used: [list agents invoked, or 'none']
- severity_indicators: [list any detected: auth, crypto, payment, database-migration, etc.]
- complexity_indicators: [list any detected: state-machine, external-api, async-patterns, etc.]

Detection rules for severity_indicators:

  • Scan Files for: auth, login, password, session, token, jwt, crypto, encrypt, secret, payment, billing, migration, permission, api_key
  • If any found, add to severity_indicators list

Detection rules for complexity_indicators:

  • Check for: state machines, external API calls, async/await patterns, database queries, caching logic
  • If any found, add to complexity_indicators list

This metadata enables the review skill to route to LIGHTWEIGHT or FULL review.

Report: ✅ Implementation complete. Status: [STATUS]