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reflect

Review completed work and identify evidence that the development workflow itself should improve.

Purpose

Projects produce lessons.

Most lessons belong to the project.

Some reveal reusable weaknesses in the workflow.

Reflect identifies the difference and proposes improvements without changing Pathfinder automatically.

Reflect also evaluates its own effectiveness. When the reflection process itself proves inadequate, it may propose improvements to this skill.

Projects produce lessons. Pathfinder keeps the reusable ones.

When to use

Use Reflect after meaningful work such as:

  • completing a significant feature
  • resolving a difficult bug
  • finishing a migration or refactor
  • completing a project phase
  • receiving significant human correction
  • discovering repeated workflow friction
  • encountering a surprising failure or assumption
  • discovering that Pathfinder guidance was incomplete or ineffective

Do not invoke Reflect after every trivial change.

Reflection should produce signal, not ceremony.

Goal

Answer two questions:

What did this execution teach us that could make a future execution better?

And:

Did the reflection process itself work well enough to discover that?


Part 1 — Reflect on the work

1. Reconstruct what happened

Review the relevant work and available evidence.

Inspect where relevant:

  • plans
  • implementation
  • tests
  • verification results
  • debugging history
  • user corrections
  • rejected or abandoned approaches
  • resulting documentation
  • relevant commits or diffs
  • existing Pathfinder guidance

Do not rely on vague recollection when repository evidence is available.

Distinguish what actually happened from what was intended to happen.

2. Identify learning signals

Look specifically for:

  • incorrect assumptions
  • repeated mistakes
  • unnecessary work
  • missing verification
  • weak verification
  • steps performed too early or too late
  • information that should have been discovered sooner
  • human corrections
  • repeated manual intervention
  • useful techniques discovered during the work
  • limitations in an existing Pathfinder skill
  • gaps between Pathfinder’s intended workflow and what actually happened
  • cases where an existing rule prevented a problem
  • cases where following existing guidance still produced a poor result

Success alone is not evidence that the workflow was good.

Failure alone is not evidence that the workflow must change.

3. Separate local knowledge from reusable learning

Classify each finding as one of:

PROJECT

Specific to this repository, stack, business domain, architecture, environment, or team.

Keep it with the project.

Examples:

  • a particular API requires a custom header
  • this repository uses Vitest rather than Jest
  • this service must start before another service
  • a framework-specific workaround is required

WORKFLOW CANDIDATE

Potentially useful across unrelated projects.

Examples:

  • implementation began before existing behavior was established
  • verification covered the happy path but ignored known edge cases
  • debugging continued before the failure was reliably reproduced
  • an undocumented dependency should have been discovered during system analysis
  • the agent repeatedly needed human correction for something the workflow could have surfaced earlier

NOISE

Interesting but not useful enough to preserve.

Discard it.

Not every observation deserves memory.

4. Test generality

For every WORKFLOW CANDIDATE ask:

  • Would this still make sense with another programming language?
  • Would it still make sense with another framework?
  • Would it still make sense in another business domain?
  • Is it solving a recurring class of problem rather than this exact incident?
  • Is Pathfinder responsible for this part of the process?
  • Would following this guidance generally improve future work?
  • Could the proposed rule unnecessarily constrain unrelated projects?

If the lesson fails these tests, keep it project-specific.

Generalize behavior, not technology.

5. Check for existing coverage

Before proposing anything new, inspect the existing Pathfinder workflow and skills.

Determine whether the lesson is already covered.

Prefer improving an existing mechanism over adding another one.

Use this order:

  1. already covered — no change
  2. clarify existing documentation
  3. improve an existing skill
  4. add or strengthen a workflow invariant
  5. create a new skill only when it represents a distinct reusable operation

Avoid duplicate skills.

Do not respond to every failure by adding another instruction.

6. Require evidence

Every proposed Pathfinder improvement must include:

Observation

What happened?

Evidence

What concrete part of the execution demonstrates it?

Generalization

Why could this recur outside this project?

Current gap

Why does Pathfinder not already handle it?

Proposed change

What is the smallest change that would address it?

Risk

How could this rule become harmful, redundant, overly restrictive, or too specific?

Validation

How could future work demonstrate that the improvement actually helped?

Do not promote intuition into workflow policy without evidence.

7. Prefer the smallest durable improvement

Possible outcomes include:

  • no change
  • project documentation update
  • AGENTS.md clarification
  • existing skill improvement
  • workflow invariant
  • new skill candidate

The best reflection may conclude that Pathfinder should not change.

Every improvement adds maintenance and context cost.

An improvement should remove more uncertainty than complexity it introduces.


Part 2 — Reflect on Reflect

Reflect is subject to the same evidence standard it applies to Pathfinder.

After completing the primary reflection, evaluate the quality of the reflection process itself.

This is bounded recursive self-improvement.

Its purpose is not to endlessly rewrite Reflect.

Its purpose is to discover whether Reflect systematically failed to do its own job.

8. Evaluate reflection quality

Ask:

  • Did Reflect miss an important signal that was visible in the evidence?
  • Did Reflect overgeneralize a project-specific issue?
  • Did Reflect classify reusable knowledge as project-specific?
  • Did Reflect propose something Pathfinder already covers?
  • Did Reflect recommend unnecessary new rules or skills?
  • Was the evidence requirement too weak?
  • Were recommendations actionable?
  • Was the reflection disproportionately verbose for the value produced?
  • Did Reflect confuse an outcome with evidence?
  • Did Reflect identify symptoms rather than the underlying workflow problem?
  • Did a human reject or substantially correct the reflection?
  • Has the same weakness appeared in previous uses of Reflect?

Do not search for a self-improvement merely because this section exists.

“No improvement needed” is a valid and desirable result.

9. Identify Reflect improvement candidates

If the reflection process itself demonstrated a meaningful weakness, classify it as:

REFLECT IMPROVEMENT CANDIDATE

This classification is reserved for improvements to reflect/SKILL.md itself.

Do not use it for general Pathfinder improvements.

For each candidate provide:

Observed weakness

What was inadequate about Reflect’s behavior or reasoning?

Evidence

What concrete output, omission, human correction, or repeated failure demonstrates the weakness?

Root cause

What part of the current Reflect process allowed the weakness?

Proposed change

What is the smallest change to reflect/SKILL.md that could improve future reflections?

Regression risk

Could the change make Reflect:

  • more verbose
  • more rigid
  • more repetitive
  • biased toward finding problems
  • prone to overgeneralization
  • excessively conservative
  • more expensive in context or execution time

Validation

What future behavior would demonstrate that the modification actually improved Reflect?

Do not recursively optimize stylistic preferences, wording preferences, or isolated cosmetic issues.

Self-improvements must materially improve reflection quality.

10. Evidence levels for self-improvement

Treat evidence for changes to Reflect according to three levels:

Level 1 — Incident

One reflection exposed a plausible weakness.

This may justify an improvement candidate.

It does not establish a general pattern.

Level 2 — Pattern

The same weakness has appeared across multiple reflections or required repeated human correction.

This provides stronger justification for changing Reflect.

Level 3 — Validation

A proposed change addresses the weakness and subsequent reflections demonstrate better behavior without obvious regression.

This is the strongest evidence that the improvement should remain.

When history is available, prefer patterns over isolated incidents.

Do not fabricate historical evidence.

11. Bound the recursion

Reflect may perform only one self-evaluation pass per invocation.

The recursion is:

Work → Reflect on work → Reflect on Reflect → Stop

Do not perform:

Reflect → Reflect on Reflect → Reflect on the reflection of Reflect → continue recursively

Further improvement must happen through a future invocation with new evidence.

Recursive improvement should accumulate evidence across executions, not consume the current execution with unlimited meta-analysis.


Promotion rules

Pathfinder improvements

Reflect proposes.

Humans promote.

Do not silently modify Pathfinder’s workflow, AGENTS.md, skills, templates, principles, or other durable guidance unless explicitly asked to implement an accepted recommendation.

Reflect self-improvements

The same rule applies to Reflect itself.

Reflect may propose changes to reflect/SKILL.md.

It must not automatically rewrite its own skill definition unless the human explicitly approves implementation.

Self-reference does not lower the evidence threshold.

It raises it.


Output

Return only sections that contain meaningful information.

Do not inflate the output to satisfy the template.

What happened

A concise reconstruction of the relevant execution.

What we learned

The important findings and supporting evidence.

Classification

For each meaningful finding:

  • PROJECT
  • WORKFLOW CANDIDATE
  • NOISE

Omit trivial noise when it adds no value.

Pathfinder gaps

Only genuine gaps not already covered.

If none exist, say so.

Rank recommendations from highest to lowest value.

For each recommendation provide:

  • target
  • proposed change
  • evidence
  • expected benefit
  • risk of overgeneralization
  • validation approach
  • confidence

No-change findings

Mention important observations that should not modify Pathfinder and explain why.

Reflect self-evaluation

Briefly assess whether this reflection process itself performed adequately.

If no material weakness was discovered, state:

No Reflect improvement proposed.

Do not invent one.

Reflect improvement candidates

Include this section only when evidence supports changing reflect/SKILL.md.

For each candidate provide:

  • observed weakness
  • evidence
  • evidence level
  • root cause
  • proposed change
  • regression risk
  • validation
  • confidence

Principles

Execution is evidence.

Projects produce lessons. Pathfinder keeps the reusable ones.

Prefer improving an existing rule over adding a new one.

Generalize behavior, not technology.

Reflect proposes. Humans promote.

Reflect is subject to the same evidence standard it applies to Pathfinder.

Self-reference does not lower the evidence threshold.

An improvement is not successful because it sounds better. It is successful because it performs better.

Every improvement should remove more uncertainty than complexity it introduces.

A workflow that cannot learn will repeat its mistakes.

A workflow that learns everything will become unusable.

Recursion should accumulate evidence, not meta-analysis.