hoodgrow-mcp

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

The description adds substantial context beyond the annotations, disclosing that tokens are currently pre-launch with zero minted supply, no price, liquidity, or holders, and that the status becomes 'live' automatically based on on-chain supply. This is valuable behavioral information that annotations alone do not convey, and it fully aligns with annotations (readOnly, openWorld, idempotent).

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 compact and well-structured: the first sentence states the core purpose and scope, and the second provides a crucial pre-launch caveat. Every sentence earns its place, with no redundancy or unnecessary detail.

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?

Despite having no output schema, the description fully explains the return value (token metadata fields plus status), the chain context, and the liveness semantics. It also provides operational context (pre-launch supply, when status flips) that makes the tool's behavior complete for an agent to correctly interpret and use.

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 tool has zero parameters, so the baseline is 4. The description meaningfully explains what the tool returns (verified metadata and liveness signal) and the semantic meaning of the output, which compensates for the lack of explicit output schema. It does not need to describe parameter syntax, as there are none.

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 the tool as a registry for B20 native-equity tokens on Base mainnet (chain 8453), listing the specific metadata fields (symbol, name, decimals) and a liveness signal. It distinguishes this from sibling tools like get_token by focusing on a fixed set of known tokens and a registry-style return, making the purpose unambiguous.

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 provides strong contextual guidance, including the pre-launch warning and the automatic status flip based on on-chain totalSupply(). It tells users not to treat pre_launch entries as tradable, which is a clear when-not-to-act guideline. However, it does not explicitly mention alternatives or when to use other sibling tools, so it stops 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?

The description adds rich behavioral detail beyond annotations: prices are read from Chainlink feeds on-chain, refreshed every 15 minutes, responses are snapshots with observedAt age, supply is corporate-action adjusted using ERC-8056 uiMultiplier, priceSource indicates feed resolution vs fallback, and catalog detection runs every minute ahead of the official registry cache. This goes far beyond the basic readOnlyHint/idempotentHint annotations.

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 dense but not bloated; every sentence serves a purpose: scope, alternative tool, data source, refresh cadence, supply adjustment, fallback behavior, and caching. The main function is front-loaded, and technical details are efficiently packed. It remains readable despite its length.

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?

Given no output schema, the description compensates by explaining key response fields (observedAt, priceSource) and edge cases (fallback feeds, cache mirroring). Combined with strong annotations (readOnly, idempotent), the tool is fully understandable for correct invocation and interpretation. No gaps remain.

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?

With zero parameters, the input schema provides no parameter semantics, but the baseline for 0 params is 4. The description adds substantial meaning by clarifying response fields like observedAt, priceSource, and supply adjustment, which helps understand what the returned data represents. This exceeds the baseline.

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 states that get_catalog returns a full catalog of all stock tokens with live price, corporate-action adjusted supply, DeFi depth, and pending/recent corporate actions. It distinguishes itself from sibling get_token by noting that get_token is for a single symbol. The verb 'Get' in the name and the phrase 'Full catalog' make the scope unambiguous.

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 explicitly says 'Prefer get_token for a single symbol', providing direct guidance on when to use this tool versus an alternative. It implies use this tool when you need catalog-wide data across all tokens. This is clear, actionable usage context.

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 indicate read-only, idempotent, and non-destructive behavior. The description adds valuable context about data source, update cadence (every minute from ERC-8056 state), and the distinction between pending on-chain actions and official ledger history, with no contradiction.

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 three dense, front-loaded sentences with no redundant wording. Every clause adds useful information about scope, data source, or freshness.

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 tool with a single optional parameter and strong annotations, the description is highly complete: it explains the data source, refresh cadence, scoping behavior, and output categories. While no output schema is present, the return concept is sufficiently specified for an agent to know what to expect.

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 input schema already fully documents the 'symbol' parameter, so the baseline is 3. The description adds meaningful value by explaining the semantic distinction between providing a symbol and omitting it, reinforcing the key usage decision.

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 and resource, clearly identifying corporate actions (splits, dividends, name changes) as the subject. It distinguishes the tool from sibling token/market tools with concrete metadata about pending and recent actions.

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 explicitly explains the optional symbol parameter and its scoping behavior, providing clear context for when to use the tool. It does not name an alternative tool or explicitly state when not to use it, but the usage pattern is unambiguous and sufficient.

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 mark read-only, but the description adds valuable behavioral details: data is read on-chain and snapshotted every 15 minutes, fails on unknown symbols, and explicitly labels both roles. These go beyond the structured annotations and describe error/staleness behavior.

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 slightly long but all sentences carry meaningful information: purpose, sibling contrast, failure mode, data freshness. It is front-loaded with the core purpose, though the first sentence is a bit dense.

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 explain return content. It does explain that it returns all relevant Morpho markets and Uniswap pools, plus role labeling and snapshot timing. It lacks specifics about return fields, but given the tool's enumerative nature, it is reasonably 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?

The schema fully covers the single parameter 'symbol' with a description and example. The description adds no further parameter-specific detail beyond referencing 'one token', so schema coverage alone merits a baseline 3.

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?

Description clearly states the tool enumerates all Morpho lending markets and Uniswap V3 pools for a given token, with explicit distinction from get_catalog/get_token ('not just the single best-APY figure'). This provides a specific verb+resource and differentiates from 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?

Explicitly states when to use this tool ('full picture for comparing yield/borrow options') and contrasts with alternatives ('not just... in get_catalog/get_token'), effectively giving a when-to-use vs when-not-to-use. Also notes failure on unknown symbols, adding a caveat.

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 description discloses the refresh cadence (every 4 hours), data source (Explorer), the distinction between real mint/burn and corporate-action multiplier changes, and the failure mode for unknown symbols. This adds substantial context beyond the readOnly/idempotent annotations.

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 compact and front-loaded with the core outputs, followed by scope and data-freshness notes. Each sentence adds value without redundancy or fluff.

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?

The description covers the main metrics, data source, refresh schedule, supply-change semantics, and failure behavior. However, it lacks an explicit return format or time range for the holder-count trend, and with no output schema, a bit more detail would make it fully 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 coverage is 100% with both parameters described in the schema. The description does not add additional meaning about parameters beyond what is already present, so the baseline score of 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 clearly states it returns holder-count trend, 24h net total_supply change, and top-holder concentration for one token, using specific verbs and a defined resource (holder analytics). This distinguishes it from sibling tools like get_markets or get_ohlc.

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 clearly scopes usage to a single token ('for one token') and notes failure for unknown symbols. It implies use when holder analytics are needed, but does not explicitly name alternatives or exclusions, falling 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?

Annotations already declare readOnly/idempotent/non-destructive, lowering the bar. The description adds useful behavioral context: the 'each list' behavior of limit and the possibility of empty gainers/losers on flat markets, which complements the openWorldHint.

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 sentences, front-loaded with the main purpose and then a precise parameter detail and edge-case caveat. No filler or redundancy.

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?

The tool is simple (one optional param, no output schema) and the description covers the main behavior, the parameter semantics, and a likely edge case. It explains what the tool returns (categories of movers) sufficiently for selection and invocation.

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 covers limit fully (min, max, default), but description adds that limit 'caps each list' – applying to all four list types – which is a meaningful semantic nuance not stated in the schema. This goes beyond simple repetition.

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 states the tool returns market movers: top gainers, losers, highest 24h swap volume, and deepest liquidity. This specific verb+resource (get market movers) with concrete metrics distinguishes it from sibling tools like get_ohlc or get_slippage.

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 provides a clear context for when to use this tool (when needing market mover lists) and includes an important caveat about empty lists during flat markets. It does not explicitly name alternatives or exclusions, but the scope is clear enough.

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 declare readOnly, openWorld, idempotent, and non-destructive hints. The description adds substantial behavioral detail beyond annotations: data source (Chainlink on-chain), refresh frequency (15 min), observedAt age indicator, null volume for old buckets, corporate-action adjustment, and priceSource fallback semantics. This exceeds what annotations provide.

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 compact yet information-dense, with six sentences each contributing unique value. It is front-loaded with the core purpose and progressively layers additional behavioral details without redundancy.

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?

Given the tool's complexity, complete schema coverage, and annotations, the description is remarkably complete. It explains key output fields (volumeUsd/swapCount, observedAt, priceSource), data sourcing, error behavior, defaults, and limitations, all without an output schema. This shows a thorough understanding of the tool's behavior.

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% with descriptions for all five parameters, so the baseline is 3. The description adds value by specifying the default 30-day window, the 730-day cap, and failure on unknown symbols, which enriches the meaning of from/to and symbol beyond the schema.

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 states the tool returns OHLC price candles for backtesting, distinguishing it from siblings like get_markets or get_slippage by focusing on historical bucketed price data. The verb 'get' is implied by the tool name and the description elaborates the resource and scope.

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 provides clear usage context: intended for backtesting, defaults for from/to, a 730-day cap, and failure on unknown symbols. It does not explicitly name alternatives or state when not to use, but the purpose clarity and sibling context make the appropriate use case evident.

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 description discloses that data comes from a snapshot refreshed every 15 minutes, not read live, and is an estimate rather than a quoted/executable price. It also specifies the failure mode for unknown symbols and the likelyCrossesTick caveat, adding substantial value beyond the readOnly/idempotent annotations.

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 dense and front-loaded with the core purpose, followed by caveats and implementation details. It is slightly longer than strictly necessary but each clause adds meaningful context, so it earns a 4 rather than 3.

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, the description covers return semantics via bestPoolAddress, bestEffectivePrice, and likelyCrossesTick, as well as failure and freshness. It does not enumerate every possible response field, but the provided context is sufficient for a moderate-complexity estimation tool.

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%; the description reinforces that amountUsd is a USD-sized trade and symbol is the token/pool lookup key, but adds no new parameter syntax, formats, or constraints beyond the schema. Therefore 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 opens with 'How much a USD-sized trade would move the price, per Uniswap V3 pool this token trades on' and clarifies it also returns bestPoolAddress/bestEffectivePrice. This clearly identifies a distinct slippage-estimation function, separate from sibling market/catalog tools.

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 states 'Per-pool estimate, not an optimal multi-pool route/split' and warns that when likelyCrossesTick is set, the trade may understate slippage and advises considering TWAP splitting. This gives practical when-to-use guidance, though no sibling tool is explicitly named as an alternative.

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?

Beyond the read-only/idempotent annotations, the description discloses data provenance (Chainlink on-chain feeds), refresh rate (15 minutes), the meaning of observedAt, supply adjustment via ERC-8056, priceSource fallback behavior, and the distinction between contract state and official registry cache. This is rich, non-obvious behavioral context.

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 six sentences and moderately long, but each sentence adds meaningful information: purpose, failure mode, data source, supply adjustment, priceSource, and detection timing. It is well-structured with the main purpose first, though it could be tightened without losing value.

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?

Given there is no output schema, the description effectively enumerates the response components (live price, supply, DeFi depth, corporate actions, observedAt, priceSource) and explains key caveats like refresh rate and fallback behavior. This is remarkably complete for a tool with a single parameter.

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 only parameter 'symbol' is already fully described in the schema with example and case-insensitivity, giving 100% schema coverage. The description adds no new information about the parameter itself, merely repeating that it is a symbol. Baseline 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 opens with a specific verb and resource: 'One Robinhood Chain stock token by symbol', followed by the list of returns (live price, supply, DeFi depth, corporate actions). This distinguishes it from siblings like get_corporate_actions and get_defi, which are separate focused tools. The 'Fails for an unknown symbol' statement also clarifies behavior.

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 clearly implies this is for a single token lookup, contrasting with sibling tools that likely handle lists or specific data types. However, it does not explicitly name alternatives or state when not to use this tool (e.g., for a list of all tokens). Thus it falls short of the 'explicit alternatives' bar but provides clear context.

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 declare readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context: results are sorted newest first, each trade includes quantitative details, and limit caps the list. No contradiction with annotations, and the added information goes beyond the structured metadata.

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 two concise sentences, with the primary purpose front-loaded and parameter usage integrated naturally. There is no redundant or filler wording—every phrase contributes to understanding the tool's behavior.

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?

The description covers the tool's return fields, sorting order, and parameter behavior. Given the simple optional parameters and strong annotations, the description is fully sufficient for an agent to understand what to expect from the tool, even without an output schema.

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%, so the baseline is 3. The description mentions limit capping and symbol omission, but these are already present in the schema descriptions. It adds no new semantic value beyond the structured parameter definitions.

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 states the tool's function: returning recent large (whale) trades in specific Uniswap V3 pools, with details on side, USD size, and transaction hash. It distinguishes from siblings by explicitly focusing on trades, and the phrasing 'Omit symbol for the global feed' adds scope clarity.

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 provides clear context on how to use the tool (omitting symbol for global feed, using limit to cap results) but does not explicitly mention alternatives or when not to use the tool. There is no apparent alternative trade-related tool among the siblings, but the guidance is still clear without exclusions.

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