Skill

reflect

Mid-task self-reflection checkpoint using Serena metacognitive tools. Use when you need to pause and evaluate: "am I on track?", "have I gathered enough info?", "am I actually done?". Triggers on: completing a significant chunk of work, before claiming done, when feeling uncertain about direction, after a long sequence of tool calls, before making large code changes.

Install

npx claudepluginhub wgordon17/personal-claude-marketplace --plugin code-quality

Tool Access

This skill is limited to using the following tools:

mcp__serena__think_about_task_adherencemcp__serena__think_about_collected_informationmcp__serena__think_about_whether_you_are_donemcp__serena__summarize_changesmcp__serena__read_memorymcp__serena__write_memorymcp__serena__list_memoriesReadGlobGrep

Preview

Structured metacognitive pause using Serena's reflection tools. Forces you to stop, evaluate

SKILL.md

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Reflect — Mid-Task Self-Reflection Checkpoint

Structured metacognitive pause using Serena's reflection tools. Forces you to stop, evaluate your progress, and course-correct before continuing.

When to Use

Before large code changes — are you still aligned with the task?
After a research/exploration phase — do you have enough information to act?
Before claiming work is done — have you actually completed everything?
When the conversation has gone long — have you drifted from the original goal?
When uncertain — should you ask the user or keep going?

Reflection Sequence

Run these Serena tools in order. Each returns a structured prompt — follow its instructions before proceeding to the next.

Step 1: Task Adherence

mcp__serena__think_about_task_adherence()

Evaluates: Am I deviating from the task? Have I loaded relevant project memories? Should I stop and ask the user rather than make potentially misaligned changes?

Act on the result. If it identifies deviation, correct course before continuing. If it suggests loading memories, do so.

Step 2: Information Completeness

mcp__serena__think_about_collected_information()

Evaluates: Have I gathered all the information I need? What's missing? Can I acquire it with available tools, or do I need to ask the user?

Act on the result. If information gaps are identified, fill them before continuing.

Step 3: Completion Check

mcp__serena__think_about_whether_you_are_done()

Evaluates: Have I performed all required steps? Should I run tests? Update docs? Write new tests? Read completion-related memory files?

Act on the result. If steps remain, do them. Don't claim done until this passes.

Optional: Summarize Changes

When wrapping up a significant body of work (not just a mid-task checkpoint):

mcp__serena__summarize_changes()

Explores the diff, summarizes all changes, explains test coverage, flags dangers and breaking changes, identifies documentation needs.

Optional: Persist Reflection

If the reflection surfaces important insights (architectural decisions, gotchas, patterns discovered), persist them:

mcp__serena__write_memory(memory_name="reflections/<topic>", content="...")

Invocation Modes

Full reflection (default) — run all 3 steps in sequence:

/reflect

Targeted reflection — run only the relevant step:

Before coding: Step 1 only (task adherence)
After research: Step 2 only (information completeness)
Before claiming done: Step 3 only (completion check)
After finishing: summarize_changes only

Fallback (Serena unavailable)

If Serena MCP tools are not available (server not running, tools not enabled), perform the same metacognitive checks using extended thinking. For each step, explicitly pause and think through:

Task adherence: "Am I deviating from what was asked? Have I loaded relevant context?"
Information completeness: "Do I have all the information I need? What's missing?"
Completion check: "Have I done all required steps? Tests? Docs? Edge cases?"

The tools enforce structured reflection; without them, be explicit about reasoning through the same questions.