parse_transactionParse a Solana transaction: type, protocol, SOL/token transfers, accounts involved, and fee details.
| Name | Required | Description | Default |
|---|---|---|---|
| signature | Yes | Transaction signature (base58, 87-88 chars) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the data categories returned (type, transfers, accounts, fees) but does not mention side effects, error behavior, or dependencies such as network access. Since 'parse' implies a read-only operation and no mutations are described, this is acceptable but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the action and resource immediately, followed by a compact, comma-separated list of the parsed components. Every word earns its place with zero filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with high schema coverage and no output schema, the description adequately sets expectations by listing the categories of data returned. It does not cover edge cases like invalid signatures or error responses, but these are not critical for a basic parse operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes the sole parameter 'signature' including format and length, achieving 100% schema description coverage. The tool description adds no additional parameter-specific context, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Parse') with a clear resource ('a Solana transaction') and enumerates the extraction scope ('type, protocol, SOL/token transfers, accounts involved, and fee details'). This clearly differentiates it from the sibling tools, which are focused on analytics, signals, or wallet/token enrichment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a detailed breakdown of a specific transaction is required, but it does not provide explicit guidance on when to use this tool versus alternatives like 'query' or 'batch_enrich'. No exclusions or alternative recommendations are mentioned.
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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Several tools cluster around the same action: trending/discovery tools like feed_latest, trending_signals, runner_scan, trenches_scan, smart_money_trenches, attention_momentum, and consensus_signal heavily overlap, and perps_basis_signal, perps_cross_venue_funding, and perps_venue_comparison all cover similar venue/funding comparisons. An agent can distinguish them only by reading fine print, increasing misselection risk.
Most tools follow readable snake_case with strong domain prefixes (perps_*, stonk_*, smart_money_*, hyperliquid_*) and clear verb_noun actions for core operations like enrich_token and compare_wallets. Minor outliers like query, feed_latest, attention_momentum, and new_tokens break the pattern but remain predictable.
41 tools is well over the 25-tool threshold for a coherent agent surface. The set fragments into many micro-specialties—five stonk tools, six perps tools, and several overlapping memecoin scanners—that could be consolidated into broader composite tools without losing capability.
For a Solana token/wallet/perps intelligence platform, the surface is exceptionally broad: discovery, enrichment, due diligence, exit signals, wallet history, transaction parsing, protocol profiles, perps, stonk, and composite querying are all covered. Missing pieces are minor, such as general holder lists or raw transaction history, and can be worked around with existing tools.