SEC Ownership Graph

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct analytical question: convergence screens issuers, coalition groups filers, influence_map pairs stake with board seat, timeline sequences filings, chain traces control, path finds board bridges, snapshot gives current context, and schema is meta. Even the two activist-related tools differ by perspective (issuer-centric vs. filer-centric), and descriptions reinforce those boundaries.
Naming Consistency4/5
Nearly all names follow a consistent snake_case noun_phrase pattern (activist_convergence, influence_map, campaign_timeline, control_chain, board_interlock_path, activist_coalition, ownership_snapshot). The lone 'get_secgraph_schema' deviates with a verb prefix, but it is a minor exception and still recognizable within the same style.
Tool Count5/5
Eight tools is well within the ideal 3-15 range and each tool covers a meaningful aspect of ownership analysis without redundancy. The count feels intentional for the scope: screening, historical timeline, control tracing, interlocks, coalitions, and snapshot context.
Completeness5/5
The tool set covers the core workflows for SEC ownership graph analysis: identifying activist activity (convergence, coalition), assessing influence (influence_map, snapshot), understanding control (control_chain), and analyzing board connections (interlock_path). A schema grounding tool fills the meta-need, and there are no obvious dead ends. One could imagine a search tool, but the descriptions imply names are directly resolvable, so gaps are minimal.
Average 4.3/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond annotations by explaining the internal gate (curated activist list), its rationale (precision over recall), and what would happen without it (dominance by micro-cap founders and filing-group artifacts). This adds meaningful behavioral context beyond the readOnly/idempotent hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the primary purpose, followed by context, parameter detail, and a concrete example. Every sentence adds value and there is no redundant or filler content.
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?
Despite lacking explanations for two parameters, the description covers the tool's purpose, return contents (franchises, span, accession numbers), limitations (gate), and provides a realistic example. This is complete enough for an agent to select and reasonably invoke the tool, especially with an output schema present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly explains the `since` parameter with an ISO date format and example, but provides no guidance on `window_days` or `min_activists`. Given the input schema has no parameter descriptions (coverage 0%), the description fails to compensate for these two parameters, leaving their semantics ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description provides a specific verb ('screen') and resource ('issuers'), with clear scope (13D filings close together). It does not explicitly differentiate from sibling tools like activist_coalition, but the focus on filing timing and activist franchises is distinctive enough to imply a unique purpose.
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 frames when to use the tool ('the what is heating up screen', 'best starting point for an event-driven question'), which gives useful context. However, it does not explicitly mention alternatives or when not to use it, so it stops short of full guideline coverage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds substantial behavioral context beyond the annotations: it explains the classification categories, the abstention behavior, the reliance solely on 13D/13G dates, and includes a concrete example. This is particularly valuable given the readOnly and idempotent hints already provided, and it does not contradict any annotation.
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 detailed and includes a helpful example, with all sentences contributing meaningful information. It is slightly longer than necessary but remains front-loaded and scannable, earning a strong score.
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?
With an output schema present, the description does not need to explain return formats; it covers behavior, classifications, abstention, and data source caveats. The main gap is the undocumented 'since' parameter, but overall the description is complete enough for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It clarifies the 'company' parameter via the example 'campaign_timeline("MNRO")' and the term 'issuer,' but it entirely omits any explanation of the optional 'since' parameter, leaving its semantics ambiguous.
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 opens with a specific verb and resource: 'Show who moved first on an issuer, who followed, and who is merely index money,' then details the exact output (chronological 13D/13G filings with filer classifications). It clearly distinguishes itself from sibling snapshot tools by emphasizing that it provides a time series, not a snapshot.
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 gives clear usage context by stating that only 13D/13G filing dates are used and that board and 13F layers are snapshots, implying this tool is for chronological ownership events. It also mentions abstention when no dated filing exists. However, it does not explicitly name sibling tools or provide direct 'use X instead' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, non-destructive behavior. The description adds valuable details: it returns percent_of_class for top holders, director/officer counts, and verified >=50% control edges. It also discloses abstention when the company can't be resolved, which is beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose, and every clause adds value. No redundant information or fluff.
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?
The tool is simple with two parameters and an output schema, so the description covers the key inputs and outputs. It explains the data included, the abstention condition, and the read-only nature. Minor gaps remain around top_n semantics, but the overview is sufficient for correct invocation.
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 0%, so the description must compensate. It mentions top holders and company context, but does not explicitly define top_n or company parameters. The mapping is implied but not stated, leaving some ambiguity about the exact meaning of top_n (e.g., number of holders vs. threshold).
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 provides supporting ownership context for one issuer, listing specific components (top holders, board size, control status). It distinguishes itself from siblings by explicitly positioning itself as grounding the headline chain/path/coalition answers, which are likely from other 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 implies usage as supplementary context for chain/path/coalition investigations, and it mentions abstention if the company cannot be resolved, which is a clear condition. It doesn't explicitly name alternatives, but the context is sufficiently clear that an agent would know when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses important behavioral traits beyond the readOnly/openWorld/idempotent annotations: it abstains (abstained=True) when no verified edge exists, never fabricates chains from sub-50% or unclassified stakes, and explains per-step fields like percent_of_class, 13D accession, and institutional_value_usd (null for ~25% of issuers). This is rich, honest behavioral context.
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 well-structured with a clear first sentence, a scoped details paragraph, and concrete examples. It is longer than strictly necessary, but each section earns its place by adding behavioral or usage context. The only minor issue is that some statistics (20 of 825, 97 of 825) could be tightened without loss.
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 complexity and the presence of an output schema, the description is nearly complete: it covers abstention behavior, direction semantics, field meanings, and materiality ranking. The missing explicit explanation of `max_hops` is the main gap, but the examples and scope discussion provide enough context for correct invocation.
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 description coverage is 0%, so the description must compensate. It thoroughly explains the `direction` parameter and provides examples that clarify `company`, but it never explicitly describes `max_hops` or its default value, even though the multi-hop discussion implies its existence. Partial compensation, but not complete for all three parameters.
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 opens with 'Trace the transitive >=50% ownership control chain through a public issuer,' which names a specific verb (trace), a resource (ownership control chain), and a clear threshold (>=50%). It also defines direction='up' vs 'down' and gives concrete examples, distinguishing this from sibling graph tools like influence_map or ownership_snapshot.
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 'Scope, precisely' paragraph gives clear context: single-hop control is general-purpose, multi-hop chains are a small-cap governance signal, and most large caps have no >=50% holder and will abstain. This effectively tells the agent when to use the tool, but it does not explicitly name alternative tools or state when-not-to-use in favor of a sibling, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only and non-destructive behavior. The description adds valuable algorithmic details: scrubbing of custodial/broker hubs, the precision discipline, and abstention behavior. It clearly explains what the tool does internally, going beyond the safety annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose. The three sentences cover purpose, methodology, and abstention, followed by an illustrative example. No wasted words; every sentence contributes to understanding.
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?
With an output schema present, the description need not detail return shape, but it still mentions 'Returns members + coalition diameter.' The tool's complexity is moderately high, and the description covers the key behavioral aspects, edge cases, and parameter semantics, making it complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explicitly explains both parameters: 'activist' is the named filer (illustrated in the example), and 'min_shared_targets' is the threshold for linking activists. The description fully covers parameter meaning, going beyond the bare schema.
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 opens with a specific verb+resource: 'Find the de-facto activist coalition (wolf-pack) around a named 13D filer.' It clearly distinguishes what the tool does and includes a concrete example, making the purpose unambiguous even without explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (to find coalitions around a filer) and provides an edge-case condition ('Abstains when the filer sits in no multi-member coalition'), but it does not explicitly mention alternative tools or when-not-to-use scenarios. Usage is inferred rather than explicitly contrasted with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare the tool read-only, idempotent, and non-destructive. The description goes further by explaining the traversal behavior (walks SHARES_DIRECTOR edge, returns alternating company chain and director per hop) and the abstain condition when no path exists. This provides useful behavioral context beyond what annotations offer.
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 well-structured with a clear opening, a bolded usage warning, and an illustrative example. It is slightly verbose but every section adds value, making it an efficient and purposeful text.
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?
With an output schema present, the description doesn't need to detail return values. It covers the tool's purpose, the domain insight about always-connected boards, the traversal behavior, and the abstain condition, making it complete for a graph traversal tool with minimal complexity.
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 description coverage is 0%, so the description must compensate. The example ('board_interlock_path("AAPL", "JPM")') clarifies from_company and to_company, but max_hops is only implicitly referenced ('within max_hops'), without explaining its meaning or default. The parameter semantics are partially covered but not fully explicit.
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 with a specific verb+resource: 'Name the director(s) who bridge two companies' boards.' It also differentiates itself from siblings by emphasizing that the output is the bridging director, not the path's existence, which distinguishes it from tools like control_chain or influence_map.
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 explicit guidance on when to use the tool (find the bridging director) and when not to (don't use it to test connectivity, since it's essentially always connected within 4 hops). It does not name alternative tools but offers a clear contextual warning that shapes usage appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and safe behavior. The description adds value by explaining the output is a curated summary, includes 'temporal-trust caveats,' and 'honest limits (CIK-only, snapshot vs dated layers, no prediction).' This goes beyond the annotations to inform the agent about content and limitations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences that immediately state the core purpose and then expand with important context. There is no fluff; every sentence adds value, and the structure is clear and front-loaded.
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?
For a zero-parameter tool with an output schema and rich annotations, the description provides sufficient context: it explains what is returned (schema, tool catalog, limits), why it exists (grounding, tool selection), and its honest limitations. This fully equips an agent to invoke the tool appropriately.
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?
The tool has zero parameters and the input schema is empty (100% coverage by default). The description does not need to elaborate on parameters. As a no-parameter tool, the baseline is 4, and no additional param semantics are required.
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 returns the 'curated secgraph ownership schema and tool catalog for grounding.' This is a specific verb+resource, and the clarification that it is 'a hand-curated summary... not a raw graph dump' distinguishes it from sibling tools that return specific analyses. The purpose is unambiguous and contextually differentiated.
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 implies usage for grounding and tool selection: 'so an agent can pick the right tool' and 'for grounding.' It also notes 'not a raw graph dump' to set expectations. While it does not explicitly name sibling tools or state when not to use, the intended use case is clear enough for an agent to decide appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds crucial behavioral context: the freshness problem with 13D filings (no exit obligation below 5%), the use of current board seats to validate old stakes, and the caveat that percent_of_class is not voting power (dual-class divergence). This goes well beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but every sentence earns its place: definition, regulatory basis, data-source rationale, freshness fix, caveat, and concrete example. It is front-loaded with the core purpose and structured logically, with no filler or redundant content.
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 of the tool and the presence of an output schema, the description covers the underlying logic, data sources, freshness issue, dual-class caveat, and expected results with a named example. It is self-contained enough for an agent to invoke correctly without additional clarification.
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 description coverage is 0%, so the description carries the full burden. It explains min_tier as a presumption tier with values 10/15/25/50 and min_value_usd as a 13F size proxy to filter out nano-caps. The limit parameter is not explicitly described, but its default and purpose are self-evident.
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 identifies issuers where a holder has a big stake AND currently sits on the board, citing a specific regulatory test (12 CFR 225.2(e)). It differentiates from simple screeners by emphasizing 'the pairing is the finding,' distinguishing it from sibling tools that might return either list independently.
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?
It explicitly recommends the tool as 'the best place to start a governance or counterparty question' and explains why the conjunction of 13D and Form 3/4/5 is uniquely valuable. It does not name specific alternatives or explicitly state when not to use it, but the context is strong enough to guide selection.
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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