Archalis Radar

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

Annotations already establish readOnly, idempotent, non-destructive, and open-world, so safety is covered. The description adds real context beyond that: it explains the data is sourced from a radar archive limited to pools found since October 16, 2026, which tells an agent results may be incomplete for older activity. It does not describe the response shape or any latency/size characteristics.

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?

A single front-loaded sentence identifies the subject, followed by the enumeration of returned data categories and a trailing coverage caveat. The list is dense but every item conveys a distinct data category. No filler sentences.

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?

No output schema exists, so the description bears the burden of explaining what comes back, and it does so by naming the concrete data categories (rug-pull outcomes, insider-seller roles, funding graph, creator network). What is missing is any sense of the response structure or how those categories are keyed. For a single-parameter lookup with full annotation coverage, this is close to adequate but not 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?

There is one parameter and schema coverage is 100%: the schema already gives the 0x-address pattern and identifies it as a BNB Chain address. The description echoes the chain ('BNB Chain wallet') but adds no format or interpretation detail beyond the schema. Baseline 3 is appropriate when the schema carries the parameter documentation.

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 a precise resource ('BNB Chain wallet') and enumerates the exact contents returned: created pools and their rug outcomes, roles held in other pools, funding relationships, and linked token creators. The verb is descriptive rather than imperative ('What the radar knows about...'), but the scope is unambiguous. Siblings (liquidity alerts, rating track record, token rating) are all token-level tools, so no confusion risk exists.

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: call this when investigating a wallet address on BNB Chain. There is no explicit statement of when to prefer this over an alternative, and no prerequisites or exclusions are given. The only guidance-adjacent content is the archive-coverage caveat, which is really a behavioral disclosure rather than a when-to-use rule.

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 readOnlyHint and idempotentHint already declaring the safety profile, the description adds real operational context beyond the annotations: polling cadence, the 24-hour discovery window, DEX coverage, and a 60-second plan-based delay. It stops short of describing ordering, pagination, or what fields each alert carries, so it is strong but not exhaustive.

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?

Three tight sentences, front-loaded with the resource and its thresholds, then scope, then the plan caveat. Every clause carries information an agent would otherwise have to guess.

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 read-only list tool with no output schema, the description conveys the alert categories and their trigger semantics, which is most of what's needed. Missing pieces are result ordering and how `limit` behaves when more alerts exist than requested.

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?

At 50% schema coverage, the description needs to compensate, and it does not: `limit` is never mentioned anywhere, and `since_minutes` is only obliquely referenced through the 'last 24 hours' scope statement (which does explain the 1440 max). The description adds almost no parameter-level meaning beyond what the schema already gives for one of the two params.

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?

States a concrete resource (liquidity alerts from a sentinel polling every ~1.5s) and the exact conditions that produce them (base liquidity down 40% or 70%+ from peak, with named alert types). An agent knows precisely what comes back without opening the schema, and the tool is clearly distinct from the wallet/rating siblings.

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 only implied: the description establishes scope (24h window, three named DEXes) but never says when to call this versus another tool or when not to call it. There are no relevant siblings to route to, which softens the gap, but no explicit guidance is given.

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?

The annotations already establish that this is a safe, read-only, idempotent, non-destructive operation. The description adds context about what the data represents—official default rates for new BNB Chain pools after first analysis—but does not address freshness, sample size, update frequency, or output structure.

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, dense sentence with no filler. It front-loads the core concept—how often pools ended in a rug pull by grade—and appends the rationale for using it.

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 zero-parameter, read-only tool with no output schema, the description sufficiently explains what the returned data conceptually represents. It could be strengthened with details about grade categories, time windows, or whether the data is current, but the core meaning is 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?

There are zero parameters, so there is no parameter semantics burden. The schema is fully described and the description provides enough conceptual framing for a no-argument aggregate lookup.

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 clearly identifies a specific analytical resource: historical default rates of new BNB Chain pools grouped by first-analysis grade. It is distinguishable from get_token_rating because it describes an aggregate track record rather than an individual token rating, though it does not explicitly name the sibling tool.

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 phrase 'so the reliability of the ratings can be judged' implies the intended use case, but it gives no explicit when-to-use guidance, prerequisites, or comparison to alternatives such as get_token_rating. Usage is inferable rather than stated.

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?

Annotations already cover readOnly/idempotent/non-destructive, and the description adds real behavioral context beyond them: unrated tokens yield rating=null with a notRated reason, D follows a rug pull, and ratings measure structural risk rather than price potential. It omits the cost/rate-limit angle (the daily fresh-analysis quota), but that is documented on the fresh parameter.

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?

Front-loaded with the rating scale, then the unrated fallback, then the caveats. It is a dense single paragraph and nearly every sentence earns its place; the closing 'Not financial advice' is the only line that does little work for an agent.

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, and the description compensates by enumerating the return payload (risk flags, simulated buy/sell taxes, contract and liquidity control, creator history, post-collapse forensics) plus the null/notRated edge case. An agent has enough to call it and interpret the result.

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 address and fresh, including the quota cost of fresh. The description adds nothing about either parameter and only enriches output semantics, 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?

States a specific resource (BNB Chain token risk rating) and defines the output scale precisely (AAA to C, SCAM, D after a rug pull), so an agent knows exactly what this returns. The resource scope is unmistakably distinct from the wallet- and liquidity-oriented siblings.

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 only implied: the description explains the unrated case and what the grades mean, which helps interpret results, but never says when to call this versus check_wallet or get_rating_track_record, nor when a fresh analysis is warranted over the archive. No exclusions or alternatives are named.

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