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Esper review

Skill sichengchen/esper/skills/esper-review

Tool-neutral, simple workflow layer for agentic, spec-driven software development. πŸͺ„βœ¨

Install
npx -y skills add sichengchen/esper --skill esper-review

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  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

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Review the current implementation against the approved increment and specs. Identifies drift, regressions, and missing spec maintenance.

SKILL.md

4.8 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

You are reviewing the current implementation against the approved increment and spec tree.

Step 1: Read context

Run esperkit context get to determine the current state.

If no active increment, tell the user: "No active increment to review. Run esper:atom or esper:batch first." and stop.

Check for an active run (active_run field). If present, this review should also consider run artifacts.

Step 2: Read the increment and specs

Read the active increment file from .esper/increments/active/<filename>. If the increment references a spec file (spec: field), read it: esperkit spec get <file> Read .esper/CONSTITUTION.md for project constraints.

If an autonomous run is active or recently completed:

  • Run esperkit run get <run-id> to read the run state
  • Run esperkit run list-tasks <run-id> to see task status
  • Run esperkit run list-reviews <run-id> to see previous review rounds
  • The review must evaluate against the frozen spec snapshot recorded in the run, not the current spec files

Step 3: Assess implementation state

Compare the current codebase state against the increment plan:

  1. Scope coverage: For each item in ## Scope, check if it has been implemented
  2. Files affected: For each file in ## Files Affected, check if the expected changes exist
  3. Verification: Run the commands in ## Verification and check results
  4. Spec alignment: Compare the implementation against the referenced spec β€” does the code match what the spec describes?

For autonomous runs, also check: 5. Task completion: Verify all task packets are marked complete 6. Review findings: Check if previous review rounds identified issues that were resolved 7. Repair coverage: Confirm repair tasks from previous rounds were addressed 8. Frozen input consistency: Verify the implementation matches the frozen spec and increment inputs, not drifted versions

Step 4: Identify issues

Check for:

  • Drift: Implementation that diverges from the increment plan (extra changes, different approach)
  • Regressions: Changes that break existing behavior documented in specs
  • Missing spec maintenance: Implementation changes that require spec updates but specs haven't been updated
  • Scope creep: Work done beyond what the increment plan describes
  • Incomplete items: Scope items not yet implemented

For autonomous runs, also check:

  • Role separation: Was the reviewer role distinct from the implementation role?
  • Stop condition compliance: Did the run respect configured limits?
  • Escalation handling: Were any escalations properly communicated?

Step 5: Write findings

Update the active increment file's ## Progress section with findings:

## Progress

### Review Findings β€” [date]
- [ok] Scope item 1: implemented as planned
- [ok] Scope item 2: implemented as planned
- [drift] Scope item 3: implementation differs β€” [explanation]
- [incomplete] Scope item 4: not yet implemented
- [spec] product/behavior.md needs updating: [what changed]

If an autonomous run is active, also persist findings as a review record: esperkit run add-review <run-id> '<review-json>'

The review JSON should include:

  • round: the review round number
  • candidate_commit: the current commit hash being reviewed
  • findings: array of finding descriptions
  • repair_tasks: array of repair task descriptions (if review fails)
  • result: "passed" or "failed"

Step 6: Recommend next actions

Based on findings:

  • If all scope items complete and verification passes: "Ready to finish. Run esper:go to complete."
  • If spec updates needed: "Run esper:sync to update specs before finishing."
  • If incomplete items remain: "Run esper:continue to resume implementation."
  • If drift detected: Present the drift and ask the user how to resolve it.

For autonomous runs with failed review:

  • Convert findings into repair tasks
  • Ask the user whether to dispatch repair tasks or escalate
  • If dispatching: create repair task packets via esperkit run add-task
  • If escalating: stop the run via esperkit run stop <run-id> 'Escalated after review'

Available CLI commands

  • esperkit context get β€” read context
  • esperkit spec index β€” show spec tree
  • esperkit spec get <file> β€” read a spec
  • esperkit increment list β€” list increments
  • esperkit run get <id> β€” read run state
  • esperkit run list-tasks <id> β€” list tasks in a run
  • esperkit run list-reviews <id> β€” list reviews in a run
  • esperkit run add-review <id> '<json>' β€” persist review findings
  • esperkit run add-task <id> '<json>' β€” create repair task
  • esperkit run stop <id> [reason] β€” stop/escalate a run

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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