Analysis Patterns

Analysis Patterns — Reusable Heuristics

> Standardized analysis methods used by multiple agents.

Tool Sequence Patterns

Productive Sequences (high correlation with quality score ≥4)

| Pattern | Description | Expected Token Cost | |---------|-------------|-------------------| | Read→Edit→Bash(pass) | Read file, edit, verify | ~1500 tokens | | Glob→Read→Edit | Find file, read, edit | ~1800 tokens | | Read→Task(sub)→Edit | Read, delegate, apply | ~2500 tokens |

Anti-Patterns (high correlation with quality score ≤3)

| Pattern | Description | Token Waste | |---------|-------------|------------| | Read→Read→Read(same) | Repeated reads of same file | ~1000 tokens/repeat | | Bash(fail)→Bash(fail)→Edit | Build-before-edit | ~800 tokens wasted | | Edit→Bash(fail)→Edit→Bash(fail) | Edit-test loop without reading error | ~1500 tokens/cycle |

Statistical Methods

Z-Score Calculation

z = (x - μ) / σ
Threshold: |z| > 2.0 → anomaly
Minimum data points: 5 (for reliable σ)

Moving Average

MA(n) = sum(last_n_values) / n
Window: 5 sessions (default)
Alert if: current > MA × 1.5

Efficiency Ratio

efficiency = productive_calls / total_calls
productive_call = call that contributed to final output (no retry, no revert)
Target: ≥ 0.85

Token Estimation Baselines

Expected token usage per tool (for waste detection):

| Tool | Expected Range | Flag If | |------|---------------|---------| | Read | 200-1500 | >2000 (large file, use offset) | | Edit | 100-500 | >800 (complex edit, consider split) | | Write | 200-2000 | >3000 (generated file too large) | | Bash | 50-500 | >1000 (verbose output, use --quiet) | | Glob | 50-200 | >500 (too many matches) | | Grep | 50-300 | >800 (broad search pattern) | | Task | 500-5000 | >8000 (sub-agent context explosion) |

Plugin Phase Patterns

Phase detection and per-plugin baselines are loaded dynamically from plugin profiles: ~/.claude/plugin-introspector/plugin-profiles/{plugin}/profile.json

When baselines unavailable ( Phase-Generic Anti-Patterns (PG-001~PG-007) are defined in > [improvement-pipeline.md](../plugin-introspector/resources/improvement-pipeline.md) Layer 2.

Improvement Signal Extraction

From Quality Evaluator

Field names match quality-evaluator.md improvement_signals[] output:

IF dimension.score ≤ 3:
  signal = {
    dimension: dimension.name,
    score: dimension.score,
    score_gap: 5 - dimension.score,
    what: "description of the issue",
    root_cause: "underlying cause",
    quantified_impact: {tokens, cost_usd, percentage_of_session},
    trace_evidence: ["trace_id: description", ...],
    suggested_change: {target_file, change_type, description},
    priority: score_gap × dimension.weight
  }

From Token Optimizer

IF waste_source.tokens_wasted > total_tokens × 0.05:
  signal = {
    type: waste_source.type,
    impact: waste_source.tokens_wasted,
    priority: impact / total_tokens
  }

From Anomaly Detector

IF alert.severity == "HIGH":
  signal = {
    type: alert.type,
    recurrence: count(similar_alerts_in_history),
    priority: recurrence > 2 ? "CRITICAL" : "HIGH"
  }

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: brody-0125
• Source: brody-0125/my-claude-skills
• License: MIT

Install and usage instructions live in the source repository linked above.