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recent_launches

$0.01: recent pump.fun launches (default last hour, mayhem excluded) with compact labels: creator prior, dev buy, bundle/insider share, unique buyers, rug flags.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
min_rsNo
max_age_sNo
only_aliveNo
exclude_mayhemNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does add useful behavior: the default time window (last hour), mayhem exclusion, and the specific compact labels returned. However, it does not disclose read-only behavior, sorting, pagination, error cases, or the meaning of '$0.01' (possibly a cost per call), leaving notable gaps.

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?

A single dense sentence packs in cost, resource, default window, filtering, and output fields with no filler. The leading '$0.01' is cryptic but not wasteful, and the colon-separated label list is efficient. Slightly better ordering might put the resource first, but the description remains highly concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list-like tool with no output schema and no annotations, the description does state what kind of data is returned and highlights two important defaults. Yet it omits parameter semantics for limit, min_rs, and only_alive; does not specify return format or ordering; and does not differentiate among sibling tools. It is adequate for a simple call but incomplete for reliable agent selection and parameter tuning.

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 explain all five parameters. It only touches max_age_s ('default last hour') and exclude_mayhem ('mayhem excluded'), both of which already have clear defaults in the schema. It gives no explanation for limit, min_rs, or only_alive, and the output label list does not clarify these ambiguous parameter names.

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 identifies the resource ('recent pump.fun launches') and the tool's output nature ('with compact labels: creator prior, dev buy, bundle/insider share, unique buyers, rug flags'). It also sets it apart from sibling tools like recent_graduations and recent_rugs by specifying pump.fun launches and the mayhem exclusion, though it does not explicitly name those alternatives.

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

Usage Guidelines2/5

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

The description implies the tool is for browsing recent launches, especially within the last hour with mayhem excluded. However, it offers no explicit guidance on when to choose this tool over siblings, no exclusions, and no alternative tool references. An agent cannot tell from the text whether to prefer recent_launches over recent_graduations or recent_rugs for a particular query.

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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TDQS

A3.7/5.0
Disambiguation5/5

Each tool serves a distinct analysis layer: market regime, launch lists, graduation/rug event lists, per-mint risk cards, creator reputation, and wallet profiling. Even the demo tool (sample_mint) is clearly framed as a preview of mint_risk_card rather than a competing endpoint.

Naming Consistency5/5

All tool names follow the same snake_case, descriptive noun-phrase pattern (creator_reputation, mint_risk_card, recent_launches). There is no mixing of verb styles or camelCase, making the toolset predictable for an agent.

Tool Count5/5

Eight tools is well within the ideal range and each tool covers a meaningful slice of the pump.fun risk-analysis domain. No tool feels redundant or purely cosmetic.

Completeness5/5

The set covers the full workflow: market context, recent launches, graduation and rug outcomes, per-mint deep dives, creator history, and wallet classification. A user can trace a launch from listing through graduation or rug and then pull entity-level context without hitting dead ends.