pumpdata

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

With no annotations, the description carries the full behavioral burden. It does disclose meaningful behavior beyond the schema: the cost ($0.005 a call, USDC on Solana over x402) and the fact that omitting payment returns an offer. However, it says nothing about read-only nature, rate limits, or response shape, leaving real gaps for a zero-annotation tool.

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 text is compact and information-dense, but it is poorly front-loaded: the vague opener 'How often it happens anyway' delays the actual purpose, and the definitional clauses are crammed into one run-on sentence. Size is reasonable, structure is not.

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 5-parameter tool with no output schema, the description explains the metrics returned (counts, multiples, median peak) and the payment flow, covering most of what an agent needs. It is close to complete, with only the absence of usage context and rate-limit details holding it back.

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?

Schema description coverage is 100%, so the schema already documents band snapping, window bounds, the venue enum, and the payment signature. The description adds definitional context ('crossing', 'peak', the 3h after-window, USD at SOL price) that reinforces but does not extend the schema, so the baseline 3 applies.

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 states concretely what is computed: how many coins first traded inside a market-cap band in a window, how many reached 2x/5x/10x/20x within 3h, and the median peak. This is specific enough to distinguish it from the sibling tools (launch_record, replay, wallet_records), though the opening sentence 'How often it happens anyway' is vague filler before the real statement.

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?

There is no guidance on when to use this tool versus the siblings, nor any stated prerequisites beyond the payment mechanics. The description implies it is an analytics/base-rate query but never says under what circumstances an agent should reach for it over replay or launch_record.

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

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

With no annotations, the description carries the full burden, and it does disclose two important traits: the $0.005 per-call cost and the USDC-on-Solana x402 payment rail. It says nothing about rate limits, latency, retry behavior, or whether the call is a pure read, and no safety profile is declared anywhere.

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 content is dense and mostly earns its place, but the parenthetical nesting is heavy and the opening sentence fragment is front-loaded with ambiguity rather than a clear verb-resource statement. The pricing sentence is a useful closer and not wasted.

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?

There is no output schema, so the description bears the return-value burden and handles it well by enumerating the returned fields (deployer record, bundle buyers and supply share, insider share, curve progress, comparable-launch quantiles). The payment/offer error flow is covered by the schema rather than the description, which is acceptable.

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?

Schema description coverage is 100%, so the schema already explains both mint and the payment PAYMENT-SIGNATURE flow (including the offer-on-missing-payment behavior). The description adds no parameter-level detail beyond implying the call is charged, so the baseline 3 applies.

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 enumerates precisely what the tool returns about a given launch: deployer history, bundle-at-creation buyers, insider share, curve progress, and comparable-launch outcomes. That makes the resource and scope unmistakable, though the opening fragment 'This launch, historically.' is cryptic and there is no explicit verb or sibling differentiation against base_rate, replay, or wallet_records.

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?

There is no statement of when to use this tool rather than base_rate, replay, or wallet_records, and no prerequisites beyond the pricing note. The payment mechanics ('leave it out to get the offer') live in the schema, not the description, so the agent gets no selection guidance from the prose itself.

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

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

With no annotations, the description carries the full burden and does so well: it discloses asynchronous queued execution and the {id, state: queued} response, the polling path, cost ($2/run, USDC on Solana over x402), failure handling (failed runs rerun free on the same id), and the simulation model (fill at the pool after latency_s, all fees and fixed costs deducted, bankroll ceilings, eight-week split). These are exactly the traits structured fields cannot convey.

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?

It is information-dense with little pure filler, but the run-on, metaphor-laden sentences ('every coin in the window counted including the dead ones') are not front-loaded and force re-reading; the operational payload (polling, price, async contract) is buried mid-paragraph rather than placed first.

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 queued job with no output schema, the description supplies the immediate return shape and redirects to replay_result for the actual results, and it covers payment, failure, and cost semantics. It is close to complete; the only gap is that the result payload itself is left entirely to the sibling tool with no hint of its shape.

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?

Schema description coverage is 100%, so per the baseline this scores 3. The prose restates the semantics of picks, latency, bankroll, exit, and payment at a high level ('Picks with timestamps and sizes in', 'filled at the pool as it stood after your latency') but adds no format, unit, or boundary detail beyond the schema — for example, the 500-item cap is only in the schema, not the description.

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 opening ('Your picks, replayed honestly' plus 'Picks with timestamps and sizes in; what they made, pick by pick and in sum') states a specific verb and resource: a backtest replay of user-supplied picks producing per-pick and aggregate P&L. It is recognizable, though the stylized phrasing means the agent has to parse a paragraph to extract a one-line purpose, and it never contrasts itself with base_rate, launch_record, or wallet_records.

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?

It gives explicit operational context: a run is a queued job returning {id, state: queued}, and the caller should 'poll replay_result with the id' — naming a sibling and the condition for using it. It also explains the payment precondition (leave payment out to receive the offer). No when-not-to-use guidance is provided, so it falls short of a 5.

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

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

With no annotations, the description carries the full disclosure burden. It does add non-schema behavior: the call is 'Free' (cost profile) and 'once done' hints at a completion/polling model. It omits permissions, whether it is read-only, and error behavior, leaving gaps.

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?

Two short clauses, front-loaded with the resource name, so it is compact. But the phrase 'once done with the execution model it charged' is dense and ambiguous, spending words without yielding clarity.

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?

With no output schema and no annotations, the description must fully explain the return payload, yet it only sketches it vaguely. An agent cannot confidently know the result's shape, whether it needs polling, or what to do with the id beyond guessing.

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?

Schema coverage is 100% for the single id parameter, so baseline is 3. The description adds only the framing that the id acts as a 'receipt' from the replay tool, a small semantic addition over the schema's 'the id from replay'.

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 names the resource (a replay's result) and enumerates what it contains (the job's state, the replay, the execution model charged), which is more than a tautology. However, it never states a clear action verb and the phrasing is cryptic, so distinguishing it from the sibling 'replay' tool requires inference.

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 id is the receipt' faintly implies the id originates from the replay tool, giving a hint of workflow. But there is no explicit when-to-use, no alternative named, and no guidance on polling vs one-shot retrieval, which is exactly the ambiguity an agent faces here.

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

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

With no annotations, the description carries the full burden and does well: it discloses the per-call cost ($0.01, USDC on Solana over x402), the 50-address batching limit, and the exact classification rules. It omits the payment-signature flow, but that is covered by the schema; what is missing is only minor read-only/reversibility framing.

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?

One dense sentence with deeply nested parentheticals makes the classification rules hard to scan. It is front-loaded and every clause carries information, but the structure is a run-on rather than cleanly segmented.

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?

There is no output schema, so the description must cover return values, and it does enumerate the returned fields (pnl_sol, put_in, took_out, coins, first_seen, class). For a three-parameter query tool with pricing and batching noted, this is nearly complete.

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?

Schema description coverage is 100%, so all three parameters are already documented, including how `mint` affects the 'new' classification. The description restates the mint semantics rather than adding meaning beyond the schema. Baseline 3 applies.

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 states a concrete resource (wallet classifications and the numbers behind them) and operation (classify each address since March 2025). It is reasonably distinguishable from siblings like launch_record and base_rate, though it never names them explicitly. The convoluted nesting makes the core purpose harder to parse than it needs to be.

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?

Usage is implied by the classification content but never stated: there is no explicit when-to-use or when-not clause, and no alternative sibling is named. It does give an operational bound ('Up to 50 addresses a call'), which is a constraint rather than selection guidance.

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