Works with the AI tools you already use
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Grok Bot+18 agentsworkflow pilot designer
Test and validate agent workflow improvements against baselines before committing to full development.
$5
workflow pilot designer
Example session with this skill installed
I want to test if adding a 'Reflector' step to my PR summary agent is worth the extra latency. Here is my current prompt and a sample diff from a complex refactor.
- Read your context and instructions
- Compiled the workflow pilot designer
- Generated the document
I have designed and executed a pilot comparison between your single-pass PR agent and the proposed 'Reflector' candidate.
Pilot Report: PR Summary Reflector
| Metric | Baseline (Single-Pass) | Candidate (with Reflector) |
|---|---|---|
| Accuracy (Key Changes) | 3/5 points captured | 5/5 points captured |
| Technical Depth | High-level overview | Detailed logic implications |
| Total Actions | 1 LLM Call | 2 LLM Calls + 1 Edit |
| Est. Latency | 4.2s | 9.8s |
| Manual Edits Needed | 2 (Missing context) | 0 |
Observation Notes
The baseline missed the critical change in the AuthMiddleware logic, focusing instead on naming conventions. The candidate identified the logic shift during the reflection step and updated the summary accordingly. While latency doubled, the candidate eliminated the need for human verification of the summary's technical accuracy.
Recommendation: Build
The candidate meets the mandatory accuracy requirements that the baseline failed. The 5-second latency trade-off is justified by the removal of manual correction cycles.
Next steps
- Implement the Reflector step as a permanent sub-task in the PR skill.
- Monitor token usage in production to ensure the cost remains within the $0.05/PR budget.
- Test on a simple documentation-only PR to ensure the Reflector doesn't over-complicate trivial changes.
workflow-pilot-designer.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
Stop guessing if your new agent architecture actually works. This skill prevents wasted engineering hours by designing and executing bounded, head-to-head pilots between a proposed workflow and a competent baseline. It moves past vague "it feels better" metrics to provide observable evidence on whether a process earns its complexity.
What it does
- Hypothesis framing identifies the specific process, intended outcomes, and realistic success criteria.
- Fair baselining defines a competent direct attempt to compare against the new candidate.
- Rubric definition creates objective quality and effort measurements before viewing outputs to prevent bias.
- Isolated execution runs both workflows in separate contexts to capture real interventions and failures.
- Evidence-based recommendation delivers a clear Build, Revise, Stop, or Inconclusive verdict based on data.
How it works
- Define the test by providing your candidate process and a representative task sample.
- Review the rubric and baseline setup generated to ensure a fair comparison.
- Execute the pilot to observe how both the baseline and the candidate handle the same inputs.
- Analyze the report to see the comparison of cost, quality, and failure points.
Frameworks & tools
Works with any agentic framework or LLM stack. It focuses on the logic of SKILL.md files, prompt chains, and tool-use sequences.
Why this beats prompting it yourself
Evaluating your own prompt improvements often leads to confirmation bias or "vibes-based" testing. This skill enforces a structured, blinded evaluation framework that accounts for hidden overhead like manual corrections and token costs.
Use cases
- Validating if a multi-step RAG chain outperforms a single long-context prompt.
- Testing if a new tool-use skill reduces manual developer intervention.
- Proving the ROI of a specialized sub-agent before full implementation.
Known limitations
Does not perform statistical significance testing. Limited to the execution environment and tools available to the current agent session.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
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Click the path to copy it. Create the folder if it does not exist yet.
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