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find_recent_changes

Read-only

Identify CFR sections modified after a specific date to locate regulatory updates in the eCFR.

Instructions

Find CFR sections that have been modified since a given date.

Uses the search API with last_modified_on_or_after filter to find sections amended after the specified date. Returns section identifiers, headings, and excerpts.

since_date must be in YYYY-MM-DD format. Results are capped at 10,000 by the API. Use title/chapter/part filters to narrow if needed.

Common pattern: find FAR changes since a specific date to check for regulatory updates that might affect ongoing acquisitions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
since_dateYes
titleNo
chapterNo
partNo
per_pageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function for the 'find_recent_changes' MCP tool. Validates inputs (since_date, title, chapter, part, per_page), then delegates to search_cfr() with query='*' and last_modified_after=since_date to find all sections modified since the given date.
    @mcp.tool(annotations={"title": "Find Recent Changes", "readOnlyHint": True, "destructiveHint": False})
    async def find_recent_changes(
        since_date: str,
        title: int = 48,
        chapter: Any = None,
        part: Any = None,
        per_page: int = 100,
    ) -> dict[str, Any]:
        """Find CFR sections that have been modified since a given date.
    
        Uses the search API with last_modified_on_or_after filter to find
        sections amended after the specified date. Returns section identifiers,
        headings, and excerpts.
    
        since_date must be in YYYY-MM-DD format. Results are capped at 10,000
        by the API. Use title/chapter/part filters to narrow if needed.
    
        Common pattern: find FAR changes since a specific date to check for
        regulatory updates that might affect ongoing acquisitions.
        """
        since_date = _validate_date_ymd(since_date, field="since_date")
        if since_date is None:
            raise ValueError("since_date is required (YYYY-MM-DD).")
        title = _validate_title_number(title, field="title")
        chapter = _validate_chapter(chapter, title_number=title)
        part = _coerce_cfr_str(part, field="part", strip_prefixes=True)
        per_page = _clamp(per_page, field="per_page", lo=1, hi=SEARCH_MAX_PER_PAGE)
    
        # Use a broad query that every section matches; eCFR requires a query term.
        return await search_cfr(
            query="*",
            title=title,
            chapter=chapter,
            part=part,
            current_only=True,
            last_modified_after=since_date,
            per_page=per_page,
        )
  • The @mcp.tool decorator registers 'find_recent_changes' as an MCP tool with the title 'Find Recent Changes'. Uses FastMCP (Python) framework.
        }
    
    
    @mcp.tool(annotations={"title": "Find Recent Changes", "readOnlyHint": True, "destructiveHint": False})
Behavior4/5

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

Annotations already provide readOnlyHint=true and destructiveHint=false. The description adds important behavioral context: date format requirement, API result cap of 10,000, and suggestion to narrow with filters. No contradictions.

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 highly concise: two lines then bullet points. Every sentence serves a purpose (purpose, mechanism, constraint, use case). No redundant or filler text.

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 5 parameters with defaults and an output schema, the description covers the key aspects: date format, result limit, filtering suggestions, and a common use case. It could optionally mention pagination behavior of per_page, but overall is complete.

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 must compensate. It explains the since_date format and implies the default title value, and mentions using filters to narrow results. It does not detail each parameter, but provides enough meaning for correct use.

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 clearly states the tool finds CFR sections modified since a given date using a search API filter. It specifies that it returns identifiers, headings, and excerpts. However, it does not explicitly differentiate from sibling tools like compare_versions or get_version_history, though the 'recent changes' focus is distinct.

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 gives a clear context for use: 'Common pattern: find FAR changes since a specific date to check for regulatory updates'. It does not explicitly mention when not to use or compare to alternatives, but the use case is well-defined.

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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