An agentic investigation system that performs deterministic analytical experiments on EDGAR financial data and general tabular datasets, emitting structured observations, evidence, and artifacts with full auditability.
Critical gaps across naming, descriptions, and schemas. Tool names lack action verbs (e.g., 'edgar_peer_comparison' vs 'analyze_peer_comparison'). Descriptions exist but are domain-jargon-heavy and lack actionable guidance for LLM selection. No parameter descriptions visible for tools accepting parameters. Error handling and recovery guidance absent. This server is below the 50th percentile for community MCP tools.
Analyze missing data patterns across specified columns.
Build a cross-sectional panel of quarterly EDGAR metrics for multiple tickers.
Compute derived financial features from an EDGAR panel or tickers.
Detect anomalies in EDGAR features using statistical methods.
Cross-sectional peer comparison via the deterministic EDGAR peer-signals computation.
Windowed trend-break detection via the deterministic EDGAR trend-break computation.
Fetch and cache SEC JSON submissions and company facts for a ticker.
12 tools have empty or missing input schemas ({}).
Tool names lack action verbs. 'edgar_peer_comparison' should be 'analyze_peer_comparison' or 'compare_peers'. LLMs infer intent from verb-noun structure; current names are ambiguous.
Descriptions are domain-jargon-heavy ('deterministic EDGAR peer-signals computation', 'windowed trend-break detection') without explaining WHEN to use the tool or WHAT the LLM should expect. Baseline: 194 chars avg, 50-200 chars optimal for LLM selection.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 37 | 2026-07-28+ | v2 |
Generate a narrative report from EDGAR analysis results.
Summarize every column: dtype, role, missingness, distinct counts, numeric stats.
Resolve a ticker symbol to CIK and company metadata via SEC EDGAR.
Execute the full EDGAR analysis pipeline: resolve, fetch, build panel, compute features, detect anomalies, generate report.
Descriptive statistics and shape of a numeric column.
No parameter descriptions visible for tools with parameters (summarize_distribution, analyze_missingness, resolve_company, fetch_company_data, build_panel, compute_features, detect_anomalies, generate_report, run_pipeline).
No error handling or recovery guidance visible. Tools do not indicate what to do on failure, whether errors are retryable, or how to self-correct. Agents cannot plan recovery.