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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Delete (Soft) Research Report

delete_report
DestructiveIdempotent

Soft-delete a report owned by the caller: status flips to delisted, visibility to private — not a hard delete, the row and R2 artifact are preserved (90-day audit window). Idempotent (deleting an already-delisted report succeeds). Sample tier rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
report_idYesId from `create_report` or `list_my_reports`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_metaYesProvenance envelope — data lineage for every MCP response
statusYes
report_idYes

TDQS

A4.3/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds significant behavioral context beyond annotations: it specifies the soft-delete nature, audit window (90 days), ownership requirement, and idempotency (deleting already-delisted succeeds). No contradiction with annotations (destructiveHint=true, idempotentHint=true are confirmed).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with dense information, front-loading the key effect. However, the inclusion of 'Sample tier rejected' is somewhat confusing and could be removed or explained, slightly reducing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (soft delete with audit window), the description covers ownership, state changes, preservation, and idempotency. Output schema exists but not shown. Minor gap: does not explain error cases or the 'Sample tier rejected' reference. Overall very complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with a clear description for report_id ('Id from create_report or list_my_reports'). The description adds no further parameter details beyond the schema, meeting the baseline. No extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it performs a soft delete, specifying exact state changes (status to delisted, visibility to private) and distinguishing from a hard delete by noting preservation of row and R2 artifact for 90 days. It also mentions idempotency, which differentiates it from other delete tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly states that the tool soft-deletes a report owned by the caller and that it is not a hard delete, providing context for when to use it (temporary removal). However, it does not explicitly mention alternatives like restore_deleted or when not to use it, so it misses explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0
Disambiguation5/5

Each tool has a distinct purpose with detailed descriptions that clarify differences. Overlaps like get_peer_comparables vs screen_universe are well-differentiated by scope (single company vs cross-sectional). Similarly, get_insider_sentiment vs get_smart_money_flow are clearly distinguished by data sources and methodology.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., create_report, get_financial_ratios, delete_alert). No mixing of conventions or inconsistent verbs.

Tool Count2/5

With 69 tools, the count far exceeds the 25+ threshold for 'too many'. While the domain is broad, the sheer volume likely overwhelms agents and increases selection complexity.

Completeness4/5

The tool set covers a wide range of SEC filings, ratios, smart-money data, alerts, reports, and more. Minor gaps exist (e.g., no options or detailed debt data), but most analyst workflows are supported.