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SKILL verified MIT Self-run

Agent Reviewer

skill-fatih-developer-fth-skills-agent-reviewer · by fatih-developer

After an agentic task completes, perform a retrospective analysis across 6 dimensions (goal alignment, efficiency, decision quality, error handling, communication, reusability). Score performance, identify inefficiency patterns, evaluate skill usage, and produce actionable improvement recommendations. Triggers on 'how did it go', 'retrospective', 'review performance', 'what could be better', or a…

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Install

$ agentstack add skill-fatih-developer-fth-skills-agent-reviewer

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

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Reliability & compatibility

✓ Security review passed
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● 3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
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About

Agent Reviewer Protocol

Task is done — now look back. What went well, what went wrong, what should be different next time? Goal: never repeat the same mistake and continuously improve skills and processes.

Core principle: Retrospectives are painful but necessary. A good agent evaluates itself.


6 Review Dimensions

1. Goal Alignment

Did the result match the original intent?

  • Was the user's actual request met?
  • Did scope creep occur?
  • Over-delivery or under-delivery?

2. Efficiency

Did the task take longer than necessary?

  • Unnecessary tool calls?
  • Repeated operations?
  • Sequential steps that could have been parallel?
  • Token/resource waste?

3. Decision Quality

Were decisions well-reasoned?

  • Were assumptions verified?
  • Were alternatives considered?
  • Did early decisions cause later problems?

4. Error Handling

How were errors addressed?

  • Detected quickly?
  • Right strategy applied?
  • Same error repeated?

5. Communication

How was user interaction quality?

  • Unnecessary confirmations requested?
  • Critical information missing at key points?
  • Too many or too few questions?

6. Reusability

Can lessons from this task transfer to the next?

  • General patterns discovered?
  • Which skills were missing or insufficient?
  • Which decisions should become standard?

Finding Severity

| Severity | Meaning | Action | |----------|---------|--------| | CRITICAL | Endangered the task or significantly reduced quality | Must fix | | MODERATE | Created inefficiency but didn't break the result | Improve | | POSITIVE | Something that went better than expected | Repeat, standardize |


Output Format

AGENT REVIEWER — Task Retrospective
Task     : [task name]
Score    : X/10
Findings : N critical | N moderate | N positive

## Dimension Scores

| Dimension | Score | Summary |
|-----------|-------|---------|
| Goal Alignment | X/10 | ... |
| Efficiency | X/10 | ... |
| Decision Quality | X/10 | ... |
| Error Handling | X/10 | ... |
| Communication | X/10 | ... |
| Reusability | X/10 | ... |
| **Overall** | **X/10** | |

## Critical Findings
[If any — what happened, why critical, how to prevent]

## Improvement Areas
[Inefficiencies, missed opportunities]

## What Went Well
[Decisions and approaches worth repeating]

## Action Items

### For Next Task
1. [Concrete change — what to do]
2. [Concrete change]

### Skill / Process Improvement
1. [Which skill should be updated / added]
2. [Which pattern should be standardized]

## Lessons Learned
[Items a future agent instance should know — candidates for memory-ledger]

Inefficiency Patterns — Auto-Detect

Scan the task history for these patterns:

| Pattern | Symptom | Fix | |---------|---------|-----| | Repeated tool call | Same file/API read 2+ times | Cache it | | Unnecessary confirmation | Low-risk step triggered approval | Adjust checkpoint-guardian threshold | | Late assumption discovery | "Actually it should be..." after error | Trigger assumption-checker earlier | | Sequential parallel steps | Independent steps ran sequentially | Use parallel-planner | | Blind retry | Logic error treated as transient | Fix error-recovery categorization | | Context loss | Previous step info forgotten | Memory-ledger not updated | | Over-decomposition | 2-step task split into 8 | Adjust task-decomposer granularity |


Skill Performance Evaluation

Evaluate skills used during the task:

## Skills Used

| Skill | Used? | Effective? | Notes |
|-------|-------|------------|-------|
| task-decomposer | Yes/No | Good/Fair/Poor | ... |
| checkpoint-guardian | Yes/No | Good/Fair/Poor | ... |
| assumption-checker | Yes/No | Good/Fair/Poor | ... |
| tool-selector | Yes/No | Good/Fair/Poor | ... |
| parallel-planner | Yes/No | Good/Fair/Poor | ... |
| error-recovery | Yes/No | Good/Fair/Poor | ... |
| memory-ledger | Yes/No | Good/Fair/Poor | ... |
| output-critic | Yes/No | Good/Fair/Poor | ... |

Missing / untriggered skills and why?

When to Skip

  • Task was single-step or under 5 minutes
  • Prototype / experimental task
  • User said "no retrospective needed"

Guardrails

  • Be honest, not kind — the value is in finding problems, not hiding them.
  • Concrete suggestions only — "do better" is useless; "cache file reads to avoid 3 redundant calls" is actionable.
  • Cross-skill: this is the ecosystem's feedback loop — findings here should update other skills and processes.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.