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Get Policy-Trade Overlap

get_policy_trade_overlap
Read-only

Identify trades by a politician near an executive order signing affecting the traded sector. Returns overlap details with date distance and match strength.

Instructions

For a single politician, list trades that occurred within a window of days before or after the signing of an executive order affecting the traded sector. Each row contains the trade, the nearestEvent, daysDelta (negative = traded N days before EO signing, positive = traded N days after), matchBasis, and matchCount, plus a summary (totalFlags, totalEstimatedUsd, topSector). Defaults to trades 1-14 days BEFORE signing; same-day trades are always excluded (intraday ordering is unknowable). Unlike get_donor_trade_overlap, executive-branch (exec-) slugs return REAL data here: both congressional and executive trade sources feed the overlap computation. IMPORTANT: matches are sector-level co-occurrence — the official traded a stock in a sector the executive order affects, within a window of its signing date. Sector matches are broad and many trades will coincide with policy activity by chance; a match is a starting point for research, not evidence of foreknowledge. The matchBasis field describes match strength only ('sector' = broad sector match), never culpability, and matchCount shows how many EOs matched in the window (a noise indicator).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesPolitician URL slug — congressional ("sen-nancy-pelosi", "rep-...") or executive branch ("exec-...")
limitNoMaximum results to return (default: 50, max: 100)
offsetNoPagination offset (default: 0)
windowNoMatch window in days around the EO signing date (default: 14, max: 30)
directionNoWhich side of the signing date to include: 'before' (default), 'after', or 'both'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
Behavior5/5

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

The description is highly transparent beyond the readOnlyHint annotation. It explains that matches are sector-level co-occurrence, the meaning of daysDelta, matchBasis (only 'sector'), and matchCount as a noise indicator. It also warns about chance matches and clarifies that executive-branch slugs return real data.

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 but somewhat verbose. It front-loads the key purpose, then details, contrast, and warnings. Every sentence adds value, but some redundancy could be trimmed (e.g., repeating 'sector matches are broad'). Still, it remains clear and informative.

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 of the tool and the presence of an output schema, the description covers all essential aspects: what it does, how it works, defaults, limitations, and important caveats. It does not need to explain return values. One minor gap: it might clarify that the output includes a summary field, but that is acceptable.

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%, so the baseline is 3. The description adds useful context like default window (14 days) and default direction ('before'), but does not provide significant additional semantics beyond what the schema already specifies for each parameter.

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 lists trades for a single politician within a window around an executive order signing. It distinguishes itself from get_donor_trade_overlap by noting that executive-branch slugs return real data here. The verb 'list' and resource 'policy-trade overlap' are specific.

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 defaults (trades 1-14 days before signing), excludes same-day trades, and includes a strong caveat that sector matches are broad and not evidence of foreknowledge. It contrasts with get_donor_trade_overlap but does not explicitly compare to other sibling tools like get_policy_trade_leaderboard.

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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