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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Peer Comparables

get_peer_comparables
Read-onlyIdempotent

Get ratio-based peer comparison for a company and its closest competitors. Peers are selected by matching 2-digit SIC industry code. Returns pipeline-computed ratios from up to 10 peers alongside the subject company for direct benchmarking. Ratio categories: profitability, liquidity, leverage, efficiency, per_share, owner_earnings, valuation. TTM (trailing twelve months) ratios are used when available for the most current view. Use as_of_date to compare peers at a specific historical date. PIT semantics for the figure leg are data-driven: when the ratio data carries an SEC accepted_at timestamp, as_of_date filters point-in-time by accepted_at (zero look-ahead, _meta.pit_safe=true); when it does not (today's data), the cut is by ratio.period_end (_meta.pit_safe=false). NOTE: peer SELECTION still uses CURRENT S&P 500 membership as a size/relevance ranking proxy regardless of as_of_date (W3-G2). Available on every plan — sample returns the subset covered by the sample bucket.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of peers to return alongside the subject company (1–10). Defaults to 5.
tickerYesSubject company ticker, e.g. AAPL. Peers are auto-selected by SIC code.
as_of_dateNoHistorical cutoff (canonical cross-tool date param) for the FIGURE leg: PIT by ratio accepted_at when present (latest-knowable, zero look-ahead, _meta.pit_safe=true), else by ratio.period_end (pit_safe=false). Peer SELECTION still uses current S&P 500 membership as a ranking proxy regardless of as_of_date (W3-G2).
categoriesNoRatio categories to include in the comparison. Defaults to profitability, valuation, and leverage.
period_end_beforeNoAlias of as_of_date (as_of_date preferred — the canonical name). Only include ratios with period_end on or before this date.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesOne row per company (subject + peers): ticker, cik, name, sector, industry, is_subject, ratios
noteNo
_metaYesProvenance envelope — data lineage for every MCP response
lineageNoProvenance for pipeline-derived values (ratio.parquet / factor_scores.parquet): source table + pipeline computed_at, plus a pointer to the tools that return filing-level lineage. NOT point-in-time (recomputed on each pipeline run).
subjectYesSubject ticker the peer set is built around
as_of_dateNo
categoriesYesRatio categories included in each peer panel
peers_returnedYes
subject_ratiosNoThe subject company's ratio panel
period_end_beforeNo

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and idempotent. The description adds significant behavioral details: PIT semantics for as_of_date, peer selection methodology, TTM ratio usage, and plan availability. It even flags a known limitation (W3-G2). No contradiction with annotations. The description enhances transparency beyond the structured fields.

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 longer than ideal but well-structured. It front-loads the purpose, then provides details on peer selection, categories, date semantics, and availability. Each sentence adds value, though the PIT semantics paragraph could be slightly compressed. Overall, it's efficient for the complexity.

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

Completeness5/5

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

Given the complexity (multiple parameters, output schema exists, annotations provided), the description covers all necessary aspects: purpose, methodology, date handling, plan access, and a notable caveat. The output schema handles return values, so no need to describe them. The description is complete for an AI agent to correctly invoke the tool.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds extra semantics: it explains that as_of_date is preferred over period_end_before, and clarifies the PIT behavior for as_of_date. It also notes the default categories. This additional context elevates the score to 4.

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 the tool's purpose: 'Get ratio-based peer comparison for a company and its closest competitors.' It specifies the selection method (matching 2-digit SIC code) and the output (pipeline-computed ratios). This distinguishes it from siblings like get_financial_ratios, which provide raw ratios without peer comparison. The verb 'get' and resource 'peer comparables' are precise.

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 provides clear context on when to use the tool: for ratio-based peer benchmarking. It explains peer selection and gives a caveat about S&P 500 membership being current regardless of as_of_date. However, it does not explicitly state when not to use it or mention alternative tools for similar purposes, such as get_financial_ratios for raw data. Slight lack of 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.

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