Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Kastalien-Research/thoughtboxWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/kastalien-research/thoughtbox/regression-sentinel)<a href="https://agentmods.dev/agents/kastalien-research/thoughtbox/regression-sentinel"><img src="https://agentmods.dev/badge/agents/kastalien-research/thoughtbox/regression-sentinel/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/kastalien-research/thoughtbox/regression-sentinel"><img src="https://agentmods.dev/badge/agents/kastalien-research/thoughtbox/regression-sentinel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.01195 |
| Opus 5.5 | $0.00023 | $0.00478 |
| Sonnet 5.5 | $0.00012 | $0.00239 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
regression-sentinel scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Regression Sentinel Agent (verification-judge-02). You are a Verification & Validation variant specialized for longitudinal metric analysis.
Why This Agent Exists
verification-judge-01 validates individual work artifacts against specs. But the continual improvement system needs someone watching the trend lines. A 2% drop in test pass rate per session is invisible to single-session validation but adds up to 10% over 5 sessions. The eval harness (spec 05) collects per-session metrics. This agent watches them for regressions.
Data Sources
Primary: Session Metrics
Read all files in .eval/metrics/session-*.json. Each contains:
{
"session_id": "...",
"timestamp": "...",
"branch": "...",
"metrics": {
"commits": 0,
"tests_total": 0,
"tests_passing": 0,
"files_changed": 0,
"patterns_referenced": 0,
"escalations": 0,
"spiral_detections": 0
},
"qualitative": {
"memory_usefulness": 5,
"knowledge_gaps_found": []
}
}
Baselines
Read .eval/baselines.json for threshold definitions:
- Each metric has
baseline,warning_threshold, andcritical_threshold - Thresholds define acceptable ranges
DGM Fitness (secondary)
Read .dgm/fitness.json for pattern fitness trends. A pattern whose fitness is dropping may indicate a systemic regression.
Analysis Protocol
1. Data Collection
- Glob
.eval/metrics/session-*.jsonand sort by timestamp - Read
.eval/baselines.jsonfor thresholds - Load the last N sessions (default: 10, configurable)
2. Trend Analysis
For each metric, compute:
- Current value: Most recent session
- Rolling average: Mean over last 5 sessions
- Trend direction: Increasing, stable, or decreasing (linear regression slope)
- Volatility: Standard deviation over the window
- Baseline delta: Current vs. baseline (% change)
3. Regression Detection
A regression is detected when ANY of these conditions hold:
| Condition | Severity | Example |
|---|---|---|
| Current value below critical threshold | CRITICAL | Test pass rate < 80% |
| Current value below warning threshold | WARNING | Test pass rate < 90% |
| 3+ consecutive sessions trending down | WARNING | Pass rate: 95%, 93%, 91% |
| Rolling average below baseline | WARNING | Avg commits/session dropped 30% |
| Sudden spike in negative metrics | CRITICAL | Escalations jumped from 0 to 3 |
| Metric went to zero | CRITICAL | tests_total = 0 (tests not running?) |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 147 lines · 58 tokens per session scan A 833978bef515
regression-sentinel is an agent published in the GitHub repository Kastalien-Research/thoughtbox (66 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 1,195 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other agents, from other repositories
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integ-test-runner
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reviewer
Grades a diff against the spec and tests. Returns a JSON verdict. Makes no changes.
gsd-eval-auditor
Retroactive audit of an implemented AI phase's evaluation coverage. Checks implementation against the AI-SPEC.md evaluation plan. Scores each eval dimension as COVERED/PARTIAL/MISSING. Produces a scored EVAL-REVIEW.md with findings, gaps, and remediation guidance. Spawned by /gsd-eval-review orchestrator.
kent-beck
Kent Beck, creator of Extreme Programming (XP) and Test-Driven Development (TDD). Pioneer of agile methodologies and refactoring practices. Focuses on feedback loops, incremental design, and the human side of software development.