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Jobs Trace Analyzer
ASecurityAnalyze benchmark jobs (Terminal-Bench, Harbor) in jobs/, inspect ATIF trajectory logs, tool call errors, prompt issues, timeout/circuit-breaker failures, and verifier results to identify harness bottlenecks in LibrAgent and generate evidence-based improvement plans. Trigger phrases: 'jobs 트레이스 분석', 'benchmark trace analysis', 'jobs 디렉토리 분석', '하네스 분석', '성적 감점 요인 분석', 'jobs-trace-analyzer'.
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- Added September 28, 2026
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[](https://www.skillsdirectory.com/skills/fritzprix-jobs-trace-analyzer)---
name: jobs-trace-analyzer
description: "Analyze benchmark jobs (Terminal-Bench, Harbor) in jobs/, inspect ATIF trajectory logs, tool call errors, prompt issues, timeout/circuit-breaker failures, and verifier results to identify harness bottlenecks in LibrAgent and generate evidence-based improvement plans. Trigger phrases: 'jobs 트레이스 분석', 'benchmark trace analysis', 'jobs 디렉토리 분석', '하네스 분석', '성적 감점 요인 분석', 'jobs-trace-analyzer'."
---
# Jobs Trace & Harness Bottleneck Analyzer
Analyze benchmark run trajectories stored under `jobs/<job_timestamp>/` to
pinpoint harness bottlenecks in **LibrAgent** (Builtin Tools, Prompts, Circuit
Breakers, Timeouts, Context Compaction) that degrade scores, and formulate
evidence-backed improvement plans.
**Scope:** tool sequences, observations, harness layers. **Don't care:**
model, serving engine. No harness contract broken → pattern and stop.
## Relationship to `harbor-harness-improvement-loop`
This skill is a **lighter inventory / categorization** pass over `jobs/<run>/`.
| Concern | Use |
| ------------------------------------------------ | ------------------------------------ |
| Quick pass-rate, failure buckets, tool frequency | **jobs-trace-analyzer** (this skill) |
| Evidence-backed BM → fix → rerun cycles | **harbor-harness-improvement-loop** |
Harbor’s analyzer is stricter: `verifier/reward.txt` as reward SSOT, ATIF-first
metrics, and explicit **heuristic ≠ verified failure**. Prefer that skill when
proposing product changes. Do not treat this script’s categories as causal proof.
## Workflow
### 1. Job Inventory & Automatic Trace Analysis
```bash
python .agents/skills/jobs-trace-analyzer/scripts/analyze_jobs_trace.py \
jobs/<job_timestamp> \
--output .libragent/work/trace-analysis/<job_timestamp>-analysis.md
```
Optional: `--verbose` prints per-task tool name lists.
The script reports:
- Total trials, pass rate (%), failed trial counts
- Failure categories (see below)
- Tool call frequency (ATIF-first when metadata trajectory is empty)
- `heuristic_error_observations` (keyword hits in ATIF observation text — **not**
verified tool failures)
#### Failure categories
| Category | Meaning |
| ------------------------------- | ---------------------------------------------------------------------- |
| `SUCCESS` | Reward ≥ 1.0 |
| `TIMEOUT_EXCEEDED` | Exception type contains `Timeout` |
| `NETWORK_API_ERROR` | Connection / API network exception |
| `TOOL_EXECUTION_ERROR` | Structured tool `error` fields only (rare; not observation heuristics) |
| `INITIALIZATION_OR_EARLY_ABORT` | Zero turns |
| `AGENT_LOOP_OR_STUCK` | ≥3 repeated adjacent identical tool calls (loop detected) |
| `HIGH_TURN_COUNT` | Turns > 30 without repeated-call evidence (inspect manually) |
| `VERIFIER_FAILED_WRONG_STATE` | Default failed bucket |
#### Tool extraction priority
1. `agent_result.metadata.trajectory` tool calls when present
2. Else ATIF `agent/trajectory.json` → `steps[].tool_calls[].function_name`
3. Else `metadata.tool_calls_count` (count only; names unavailable)
Reward prefers `verifier/reward.txt`, then `verifier_result.rewards.reward`.
---
### 2. Deep-Dive Trajectory Inspection (ATIF & Task Logs)
For each failed trial, inspect `jobs/<job_timestamp>/<task_name>/`:
1. **`result.json`**: rewards, `exception_info` / `exception.txt`, metadata turns
2. **`agent/trajectory.json` (ATIF)**: first divergence turn
3. **`verifier/reward.txt` & `trial.log`**: why verification failed
---
### 3. Harness Layer Mapping
> **Don't care (never diagnose, compare, or blame):** model, serving engine.
> In this harness project, tests evaluate the harness itself. If no harness
> contract (tool schema, handler, prompt assembly, circuit breaker, adapter)
> is broken, report the tool pattern and stop.
| Symptom | Primary Owning Layer | Target Code |
| ------------------------------------ | ---------------------------------- | ------------------------------------------------------------------- |
| Tool parameter / schema error | Builtin MCP tools | `src-tauri/src/mcp/builtin/` |
| Repeated tool loop | Circuit breaker / natural recovery | `src-tauri/src/agent/llm/circuit_breaker.rs`, `natural_recovery.rs` |
| Timeout / unfinished | Timeout multipliers / shell | `src-tauri/src/mcp/builtin/workspace/utils.rs` |
| Missing verification / premature end | Prompts | `src-tauri/src/agent/prompt/` |
| Context loss / truncation | Compaction | `src-tauri/src/agent/llm/completion/request/compact.rs` |
---
### 4. Formulate Evidence-Based Improvement Plan
For each issue: symptom + trajectory evidence → root cause → smallest
intervention → verification (`pnpm refactor:validate`, `cargo test`, re-run
slice). Escalate to `harbor-harness-improvement-loop` for controlled BM cycles.
---
### 5. Report Output Location
Save reports under:
`.libragent/work/trace-analysis/<job_name>-analysis.md`
Files in this skill
- SKILL.md
- scripts/analyze_jobs_trace.py
- scripts/test_analyze_jobs_trace.py
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