sdlc-confidence-reporter
Skill detail with category, linked agents, and source metadata.
sdlc-confidence-reporter
Standardizes logprob-based confidence object generation for SDLC agent outputs. Handles confidence object construction, missing logprob fallback, and needs_review flagging. Agents delegate confidence reporting to this skill instead of reimplementing the pattern.
Source: .github/skills/intelligence/sdlc-confidence-reporter/SKILL.md
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# SDLC Confidence Reporter
## Overview
Provides a standardized pattern for generating logprob-based confidence objects in SDLC agent outputs. Instead of each agent independently implementing confidence logic and fallback handling, agents invoke this skill's pattern.
## When to Use This Skill
- An agent's output includes a recommendation, decision, or claim that needs confidence scoring
- An agent needs to report whether logprobs were available at runtime
- An agent's output must comply with the confidence standard (logprob-only, no heuristic labels)
## Unitary Function
Given the runtime logprob state and the output content, produce a standards-compliant confidence object for inclusion in the agent's JSON output.
## Confidence Standard (MANDATORY)
All SDLC agents MUST follow these rules for confidence reporting:
### Prohibited Patterns
- Do NOT output heuristic confidence labels (e.g., "high", "medium", "low")
- Do NOT invent confidence percentages (e.g., "85% confident")
- Do NOT use qualitative hedging as a substitute for confidence (e.g., "we are fairly certain")
### Required Confidence Object
Every agent output that includes recommendations, decisions, or claims MUST include a `confidence` block:
```json
"confidence": {
"method": "token_logprob",
"summary_logprob": -0.15,
"avg_token_logprob": -0.08,
"min_token_logprob": -0.42,
"logprobs_available": true,
"status": "pass"
}
```
### Field Definitions
| Field | Type | Description |
|---|---|---|
| `method` | string | Always `"token_logprob"` -- the only approved method |
| `summary_logprob` | float | Log probability of the summary/recommendation token sequence |
| `avg_token_logprob` | float | Average log probability across all output tokens |
| `min_token_logprob` | float | Minimum (worst) log probability among output tokens |
| `logprobs_available` | boolean | Whether the runtime provided token logprobs |
| `status` | string | `"pass"` if logprobs available, `"needs_review"` if not |
### Fallback When Logprobs Are Unavailable
If the runtime does not provide token logprobs:
```json
"confidence": {
"method": "token_logprob",
"summary_logprob": null,
"avg_token_logprob": null,
"min_token_logprob": null,
"logprobs_available": false,
"status": "needs_review"
}
```
When `logprobs_available: false`:
1. Set all logprob fields to `null`
2. Set `status` to `"needs_review"`
3. The output MUST note that confidence scoring requires re-run in a logprob-enabled runtime
### Confidence Thresholds
| min_token_logprob | Interpretation |
|---|---|
| > -0.10 | Strong confidence -- output is well-supported |
| -0.10 to -0.30 | Moderate confidence -- output is reasonable but benefits from review |
| < -0.30 | Low confidence -- output needs review before acting on recommendations |
## Agent Integration
Agents reference this skill in their Skills section:
```
- sdlc-confidence-reporter (logprob-based confidence object generation)
```
The agent's JSON output schema inclu