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Mode VC Chart: LangChain Alternatives: Downloads vs. Newer AI SDKs

Search All Venture & AI Charts

search_charts
Read-onlyIdempotent

Searches across all 38 empirical AI & venture research charts published by Mode VC. Filter by keyword, topic, or date. Returns titles, empirical claims, takeaways, canonical URLs, and markdown endpoints.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of charts to return
queryNoSearch term matching title, claim, key takeaway, or keywords (e.g. "pre-seed", "pricing", "claude", "inference", "sdk")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds useful behavior by disclosing the returned fields (titles, empirical claims, takeaways, canonical URLs, markdown endpoints), which matters because no output schema exists. Minor gap: no pagination/result-limit behavior beyond the schema's limit.

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?

Three tightly packed sentences with zero filler, leading with the scope and action before listing filters and return fields. Every clause carries information.

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 no output schema, the description correctly picks up the burden by enumerating what is returned, and the annotation set covers the safety profile. It is nearly complete but leaves the relationship to sibling retrieval tools (e.g., get_chart_data) unstated.

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 100%, so the schema fully documents query and limit, establishing a baseline of 3. The description adds little parameter meaning and actually introduces a discrepancy: it advertises filtering "by date" although no date parameter exists in the schema, which could mislead an agent.

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?

States a specific verb ("Searches") and resource ("38 empirical AI & venture research charts published by Mode VC"), with a concrete count that bounds scope. It does not explicitly differentiate itself from siblings like get_chart_data or get_venture_chart_of_the_day, so an agent must infer the routing, but the core purpose is unambiguous.

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?

Offers implied usage ("Filter by keyword, topic, or date") but gives no when-to-use-vs-alternative guidance and no exclusions against the sibling retrieval tools. An agent can guess that this is the discovery step before get_chart_data, but nothing in the text says so.

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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