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Esper review

Skill sichengchen/esper/skills/esper-review

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

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

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 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.

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 — 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 — [date]
- [ok] Scope item 1: implemented as planned
- [ok] Scope item 2: implemented as planned
- [drift] Scope item 3: implementation differs — [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 — read context
  • esperkit spec index — show spec tree
  • esperkit spec get <file> — read a spec
  • esperkit increment list — list increments
  • esperkit run get <id> — read run state
  • esperkit run list-tasks <id> — list tasks in a run
  • esperkit run list-reviews <id> — list reviews in a run
  • esperkit run add-review <id> '<json>' — persist review findings
  • esperkit run add-task <id> '<json>' — create repair task
  • esperkit run stop <id> [reason] — stop/escalate a run

What ships with it

Read from the repository

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

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Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.