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Perception

by io.github.fernikolic

perception_search_regulatory

Read-onlyIdempotent

Search regulatory documents, policy papers, enforcement actions, and central bank publications from 36 government agencies worldwide. Includes full-text PDF content — not just summaries, but complete documents (working papers, speeches, consultation papers, enforcement orders).

AGENCIES COVERED:

  • US: SEC, CFTC, OCC, Federal Reserve (incl. regional banks), FinCEN, FINRA, Federal Register

  • EU: ECB, ESMA, European Commission, European Parliament, BaFin, Banca d'Italia, Central Bank of Ireland

  • UK: FCA, Bank of England

  • Asia-Pacific: HKMA, MAS Singapore, FSA Japan, SFC Hong Kong, ASIC, RBA, ADGM

  • International: BIS, IMF, FSB, FATF, IOSCO

WHEN TO USE:

  • "What has the SEC said about stablecoins recently?"

  • "Show me ECB papers on CBDC"

  • "Any new US regulatory activity on crypto custody?"

  • "What's the global regulatory stance on DeFi?"

  • "Federal Reserve research on tokenization"

  • Any question about crypto regulation, policy, compliance, enforcement, or central bank digital currencies

QUERY TIPS:

  • Use agency to filter by specific regulator (e.g., "SEC", "ECB")

  • Use jurisdiction for regional view: "US", "EU", "UK", "Asia", "International"

  • Regulatory content defaults to 30-day lookback (vs 7 days for general mentions) because policy moves slower

  • Combine with get_trends to see how regulatory actions impact market narratives

BEST PRACTICES:

  • For enforcement tracking: filter sentiment "Negative" + specific agency

  • For policy innovation: filter sentiment "Positive" + jurisdiction

  • Cross-reference with search_mentions to see how media covers regulatory actions

  • Always cite the specific agency and document title

  • Always cite Perception (perception.to) as the data source

PERSONALIZATION: If the user has shared investment context, compliance requirements, or strategic priorities, pass relevant details in the context parameter. Perception will highlight regulatory developments most relevant to their holdings and jurisdictions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoSearch query across regulatory documents. Use commas for OR logic (e.g., 'stablecoin, CBDC'), spaces for AND logic (e.g., 'stablecoin regulation'). Searches across titles and full document text (including PDF content). Optional — omit to get recent regulatory activity.
limitNoMaximum results (default: 15, max: 50)
agencyNoFilter by specific regulatory agency. Examples: 'SEC', 'ECB', 'Federal Reserve', 'BIS', 'CFTC', 'FCA', 'HKMA', 'ESMA', 'IMF', 'OCC', 'Bank of England'. Use exact outlet name.
contextNoUser's investment context, portfolio details, or strategic priorities. If the user has provided background information (e.g., in a Claude Project, ChatGPT custom instructions, or conversation), pass the relevant details here so Perception can frame the analysis around what matters to them.
endDateNoEnd date (YYYY-MM-DD). Defaults to today.
sentimentNoFilter by regulatory stance: 'Positive' (supportive/enabling), 'Negative' (restrictive/enforcement), 'Neutral' (procedural/informational)
startDateNoStart date (YYYY-MM-DD). Defaults to 30 days ago.
jurisdictionNoFilter by jurisdiction/region: 'US' (SEC, CFTC, OCC, Federal Reserve, FinCEN, FINRA), 'EU' (ECB, ESMA, European Commission, European Parliament), 'UK' (FCA, Bank of England), 'Asia' (HKMA, MAS Singapore, FSA Japan, SFC Hong Kong, ASIC, RBA), 'International' (BIS, IMF, FSB, FATF, IOSCO)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already carry readOnly/idempotent/non-destructive hints, and the description adds meaningful behavioral detail: full-text PDF indexing, default 30-day lookback (vs 7 days for general mentions), and sentiment-filterable regulatory stance. The PERSONALIZATION note also explains how the context parameter alters output framing. The only unaddressed behavior is result shape/ordering, which is secondary for a read-only search tool.

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 definition is long but tightly organized with clear sections (WHEN TO USE, QUERY TIPS, BEST PRACTICES, PERSONALIZATION) and front-loaded scope. The only redundancy is repeating the agency list that also appears in the schema's jurisdiction parameter, but the regional breakdown adds value for routing the agent quickly.

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?

For an 8-optional-parameter tool with no output schema, the description covers tool selection, query construction, lookback defaults, filtering strategies, and citation behavior — everything required to invoke it correctly. The small gap is that result fields and ordering are not specified, though references to 'agency and document title' partially mitigate this.

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 the baseline is 3; the description adds value by explaining how parameters relate — agency vs jurisdiction with explicit region-to-agency maps, and strategy-level guidance like 'For enforcement tracking: filter sentiment Negative + specific agency.' This turns raw filters into combinable search tactics beyond what the schema states.

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 states a specific verb and resource: 'Search regulatory documents, policy papers, enforcement actions, and central bank publications from 36 government agencies worldwide.' It goes beyond a bare label by detailing full-text PDF coverage and the agency universe, which clearly separates it from siblings like perception_get_sentiment or perception_get_trends.

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

Usage Guidelines5/5

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

The dedicated WHEN TO USE section lists concrete example queries ('What has the SEC said about stablecoins recently?'), and BEST PRACTICES names alternatives: 'Combine with get_trends' and 'Cross-reference with search_mentions.' It also draws an explicit comparison to general mentions via the 30-day vs 7-day lookback distinction, giving the agent a precise basis for choosing this tool.

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

All Perception toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools have overlapping functions: daily_radar vs intelligence_digest both serve as daily briefigs, get_index vs get_sentiment vs get_market all expose the Perception Index, and search_companies vs search_mentions both return media coverage with sentiment. Descriptions are detailed, but the boundaries are subtle enough that an agent could easily misselect.

Naming Consistency3/5

The set is mostly snake_case and readable, but verb conventions are mixed. Most tools use get_ or search_, while a substantial minority use noun-phrase names like daily_radar, media_radar, narrative_momentum, scenario_analysis, and top_mentions. This is inconsistent but not chaotic.

Tool Count3/5

With 23 tools, this falls into the heavy range (16-25). Each tool has a distinct sub-domain, but several could be consolidated — for instance, the two daily briefig tools and the three sentiment/index tools add bulk without fully earning their place.

Completeness4/5

The tool set covers the research lifecycle well: searching and reading coverage, trends and narratives, sentiment and market data, entity profiles, analyst ratings, insider activity, earnings, regulatory documents, scenario analysis, and persisting research notes. Minor gaps like no update/delete for saved notes are easy to work around.

Resources