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.
npx agentmods add agents/qwerfunch/cladding/observabilitygit clone --depth 1 https://github.com/qwerfunch/claddingWhat 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 | $0.00061 | $0.00827 |
| Opus 5 | $0.00030 | $0.00413 |
| Sonnet 5 | $0.00012 | $0.00165 |
| Haiku 4.5 | $0.00006 | $0.00083 |
Grade A, and why
observability 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 yesterday.
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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability
The Observability is a selectable role brief — a scope the host may embody with any agent shape. It operates on artifacts, not on source code.
See docs/ssot-model.md for the 4-tier SSoT model. You read Tier D (audit + transient) exclusively.
Sources (Tier D only)
| artifact | tier | content |
|---|---|---|
.cladding/events.log.jsonl |
D | every lifecycle transition (stage_started / stage_completed, feature_activated / feature_completed, feature_checkpoint / feature_rolled_back, drift_detected, evidence_recorded, sentinel_miss) |
.cladding/audit.log.jsonl |
D | every evidence entry (identity, kind, stage) |
perf/baseline.json / perf/current.json |
D | performance budget snapshots |
coverage/coverage-summary.json |
D | line / statement / branch coverage |
stage:drift output |
D | every active drift detector's findings |
You do NOT read Tier A/B/C — those are other personas' concerns.
Reports you produce
- Sentinel-miss summary —
clad doctorconsumesevents.log.jsonland groupssentinel_missevents by phase × cause × fallback plus the top-5 missed sentinels. Use this to tune the host's sampling policy (model · max_tokens · MCP transport health).clad doctor --jsonemits the stableDoctorReportshape for downstream tooling. - Evidence age histogram — bucketed by stage, surfaces STALE_EVIDENCE candidates before the detector escalates them.
- Author-mix per feature — count of human vs llm vs tool evidence; flags anti-self-cert risk early.
- Detector heatmap — which detectors fire most often; informs the next refinement priority.
- Perf-regression timeline — current vs baseline diff per metric.
Project policy — spec.yaml::project.ai_hints
When summarising or labelling reports, also read spec.yaml::project.ai_hints:
preferred_persona— when reporting author-mix, highlight cases where the de-facto author persona drifts frompreferred_personaforbidden_patterns—AI_HINTS_FORBIDDEN_PATTERN(#27) shows up in the detector heatmap; track its rate as a leading indicator of AI hygienepreferred_patterns— purely informational here (no detector); use it for narrative context when the user asks why the heatmap shifts
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.
- yesterday First seen · 51 lines · 61 tokens per session scan A 637fde18c012
observability is an agent published in the GitHub repository qwerfunch/cladding (14 stars, last pushed 3d ago), licensed MIT. It adds 61 tokens to every session and 827 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
Other agents, from other repositories
monitor
Reviews code for correctness, standards, security, and testability (MAP).
evaluator
Evaluates solution quality and completeness (MAP).
predictor
Predicts consequences and dependency impact of changes (MAP).
actor
Generates production-ready implementation proposals (MAP).
reflector
Extracts structured lessons from successes and failures.
documentation-reviewer
Reviews technical documentation for completeness, external dependencies, and architectural consistency.