ct-grade
Agent BuildingCLEO session grading and A/B behavioral analysis with token tracking. Evaluates agent session quality via a 5-dimension rubric (S1 session discipline, S2 discovery efficiency, S3 task hygiene, S4 error protocol, S5 progressive disclosure). Supports three modes: (1) scenario — run playbook scenarios S1-S5 via CLI; (2) ab — blind A/B comparison of different CLI configurations for same domain operations with token cost measurement; (3) blind — spawn two agents with different configurations, blind-comparator picks winner, analyzer produces recommendation. Use when grading agent sessions, running grade playbook scenarios, comparing behavioral differences, measuring token usage across configurations, or performing multi-run blind A/B evaluation with statistical analysis and comparative report. Triggers on: grade session, evaluate agent behavior, A/B test CLEO configurations, run grade scenario, token usage analysis, behavioral rubric, protocol compliance scoring.
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Session Grading Guide
Session grading evaluates agent behavioral patterns against the CLEO protocol. It reads the audit log for a completed session and applies a 5-dimension rubric to produce a score (0-100), letter grade (A-F), and diagnostic flags.
When to Use Grade Mode
Use grading when you need to:
- Evaluate how well an agent followed CLEO protocol during a session
- Identify behavioral anti-patterns (skipped discovery, missing session.end, etc.)
- Track improvement over time across multiple sessions
- Validate that orchestrated subagents followed protocol
Grading requires audit data. Sessions must be started with the --grade flag to enable audit log capture.
Starting a Grade Session
CLI
# Start a session with grading enabled
ct session start --scope epic:T001 --name "Feature work" --grade
# The --grade flag enables detailed audit logging
# All CLI operations are recorded for later analysis
Running Scenarios
The grading rubric evaluates 5 behavioral scenarios that map to protocol compliance:
1. Fresh Discovery
Tests whether the agent checks existing sessions and tasks before starting work. Evaluates session.list and tasks.find calls at session start.
2. Task Hygiene
Tests whether task creation follows protocol: descriptions provided, parent existence verified before subtask creation, no duplicate tasks.
3. Error Recovery
Tests whether the agent handles errors correctly: follows up E_NOT_FOUND with recovery lookups (tasks.find), avoids duplicate creates after failures.
4. Full Lifecycle
Tests session discipline end-to-end: session listed before task ops, session properly ended, CLI usage patterns.
5. Multi-Domain Analysis
Tests progressive disclosure: use of admin.help or skill lookups, use of progressive disclosure for programmatic access.
Evaluating Results
CLI
# Grade a specific session
ct grade <sessionId>
# List all past grade results
ct grade --list
Understanding the 5 Dimensions
Each dimension scores 0-20 points, totaling 0-100.
S1: Session Discipline (20 pts)
| Points | Criteria |
|---|---|
| 10 | session.list called before first task operation |
| 10 | session.end called when work is complete |
What it measures: Does the agent check existing sessions before starting, and properly close sessions when done?
S2: Discovery Efficiency (20 pts)
| Points | Criteria |
|---|---|
| 0-15 | find:list ratio >= 80% earns full 15; scales linearly below |
| 5 | tasks.show used for detail retrieval |
What it measures: Does the agent prefer tasks.find (low context cost) over tasks.list (high context cost) for discovery?
S3: Task Hygiene (20 pts)
Starts at 20 and deducts for violations:
| Deduction | Violation |
|---|---|
| -5 each | tasks.add without a description |
| -3 | Subtasks created without tasks.find {exact:true} parent check |
What it measures: Does the agent create well-formed tasks with descriptions and verify parents before creating subtasks?
S4: Error Protocol (20 pts)
Starts at 20 and deducts for violations:
| Deduction | Violation |
|---|---|
| -5 each | E_NOT_FOUND error not followed by recovery lookup within 5 ops |
| -5 | Duplicate task creates detected (same title in session) |
What it measures: Does the agent recover gracefully from errors and avoid creating duplicate tasks?
S5: Progressive Disclosure Use (20 pts)
| Points | Criteria |
|---|---|
| 10 | admin.help or skill lookup calls made |
| 10 | Progressive disclosure used for programmatic access |
What it measures: Does the agent use progressive disclosure (help/skills) for efficient protocol access?
Interpreting Scores
Letter Grades
| Grade | Score Range | Meaning |
|---|---|---|
| A | 90-100 | Excellent protocol adherence. Agent follows all best practices. |
| B | 75-89 | Good. Minor gaps in one or two dimensions. |
| C | 60-74 | Acceptable. Several protocol violations need attention. |
| D | 45-59 | Below expectations. Significant anti-patterns present. |
| F | 0-44 | Failing. Major protocol violations across multiple dimensions. |
Reading the Output
The grade result includes:
- score/maxScore: Raw numeric score (e.g.,
85/100) - percent: Percentage score
- grade: Letter grade (A-F)
- dimensions: Per-dimension breakdown with score, max, and evidence
- flags: Specific violations or improvement suggestions
- entryCount: Number of audit entries analyzed
Flags
Flags are actionable diagnostic messages. Each flag identifies a specific behavioral issue:
session.list never called-- Check existing sessions before starting new onessession.end never called-- Always end sessions when donetasks.list used Nx-- Prefertasks.findfor discoverytasks.add without description-- Always provide task descriptionsSubtasks created without parent existence check-- Verify parent exists firstE_NOT_FOUND not followed by recovery lookup-- Follow errors withtasks.findNo admin.help or skill lookup calls-- Loadct-cleofor protocol guidanceNo progressive disclosure calls-- Useadmin.helpor skill lookups
Common Anti-patterns
| Anti-pattern | Impact | Fix |
|---|---|---|
Skipping session.list at start | -10 S1 | Always check existing sessions first |
Forgetting session.end | -10 S1 | End sessions when work is complete |
Using tasks.list instead of tasks.find | -up to 15 S2 | Use find for discovery, list only for known parent children |
| Creating tasks without descriptions | -5 each S3 | Always provide a description with tasks.add |
Ignoring E_NOT_FOUND errors | -5 each S4 | Follow up with tasks.find or tasks.exists |
| Creating duplicate tasks | -5 S4 | Check for existing tasks before creating new ones |
Never using admin.help | -10 S5 | Use progressive disclosure for protocol guidance |
| No progressive disclosure calls | -10 S5 | Use admin.help or skill lookups for protocol guidance |
Grade Result Schema
Grade results are stored in .cleo/metrics/GRADES.jsonl as append-only JSONL. Each entry conforms to schemas/grade.schema.json with these fields:
sessionId(string, required) -- Session that was gradedtaskId(string, optional) -- Associated task IDtotalScore(number, 0-100) -- Aggregate scoremaxScore(number, default 100) -- Maximum possible scoredimensions(object) -- Per-dimension{ score, max, evidence[] }flags(string[]) -- Specific violations or suggestionstimestamp(ISO 8601) -- When the grade was computedentryCount(number) -- Audit entries analyzedevaluator(auto|manual) -- How the grade was computed
CLI Grade Operations
| Command | Description |
|---|---|
ct grade <sessionId> | Grade a specific session |
ct grade --list | List past grade results |