Talon

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

No annotations are provided, so the description carries the full disclosure burden. It hints at statefulness ('so the session remembers what we already did') and mutation (writes buy cards, keeps a profile), but says nothing about permissions, side effects, reversibility, or what 'No screen' constrains. Disclosure is far short of what an unannotated mutation tool needs.

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 short, but it is a chain of telegraphic fragments ('Hands fills. No screen.') rather than front-loaded prose, which makes intent harder to parse. Little is wasted in length, but structure sacrifices 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?

For a stateful multi-agent tool with zero annotation coverage, 0% parameter documentation, and no output schema, the description is not complete enough. An agent cannot confidently determine inputs, effects, or the return contract from what is written.

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 0% for both parameters. The description partially compensates by explaining that holdings and skipped are posted 'so the session remembers what we already did', but it never defines the nested shapes (symbol/address, reason/address) or the distinction between the two arrays beyond the word names.

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 agent's role ('Proactive desk') and lists coarse activities: finds useful work, maintains a me.md-style profile, writes buy cards, and hands off to 'Hands'. The verbs are present but wrapped in domain jargon ('buy cards', 'desk', 'me.md-style profile') so the actual resource acted on is ambiguous, and it does not clearly distinguish itself from the many talon_* 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?

There is an implied handoff ('Hands fills') and an implied purpose for the payload ('so the session remembers what we already did'), but no explicit when-to-use condition, no when-not, and no named alternative among the ~45 sibling tools. The agent must guess when this tool should be invoked.

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 provided, the description carries the burden of behavioral disclosure. It indicates a read-only ranking operation by saying it 'Returns' candidates and explicitly says it does not produce trade orders. However, it does not clarify whether this is strictly read-only, what 'asymmetric candidates' means in practice, or any data freshness or rate-limit considerations.

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 entire description is one compact sentence with no filler. It front-loads the main action and criteria, then adds a useful clarifying exclusion in the second clause. Every phrase earns its place.

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 one optional parameter and no output schema, the description is reasonably complete: it explains what the tool ranks and what it returns. However, it leaves key context undefined, such as what 'asymmetric candidates' means, the exact output shape, and how `limit` controls the response, which an agent may need to invoke it correctly.

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 (`limit`), and schema description coverage is 0%. The description does not mention `limit` at all or explain how it affects results. The schema provides type, default, and bounds, but the description fails to add semantic meaning, such as whether limit controls the number of ranked tokens returned or the depth of analysis.

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 specific verb ('Rank') and a clear resource ('tokens') with explicit criteria: sentiment, fundamentals, and price action alignment. It also distinguishes this tool from order-execution tools by stating it returns 'best asymmetric candidates, not trade orders,' which helps differentiate it from many talon_* 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?

The description conveys clear context for use: ranking tokens with aligned sentiment, fundamentals, and price action. It explicitly excludes trade orders, providing a useful boundary, though it does not name alternative sibling tools or give detailed when-not-to-use guidance.

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 and no output schema, the description carries the full burden of behavioral disclosure. It reveals the general output shape but does not state whether the operation is read-only, whether it has side effects, requires authentication, or has rate-limit or error behaviors. More transparency is expected for an unannotated 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?

Two concise sentences, front-loaded with the core purpose and output. Every sentence adds value, including the agent-vs-UI clarification. No redundant phrasing.

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 simple one-parameter tool, the description is mostly adequate, but the absence of an output schema and any behavioral caveats leaves gaps. An agent knows it gets a structured answer with certain categories but not the exact JSON shape or any usage limitations.

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 already fully documents the single parameter `q` as 'What you want to know' (100% coverage). The description adds the 'plain language' framing, which is useful but minimal. Baseline 3 is appropriate given high schema coverage.

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 clear verb ('Ask') and resource ('Talon'), and specifies that it returns a structured answer with named categories. It implies a general-purpose natural-language query tool, though it does not explicitly distinguish itself from the large set of sibling 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?

The phrase 'Ask Talon in plain language' implies when to use the tool, and 'Built for agents, not a UI' signals the intended caller. However, it gives no explicit exclusions or alternatives among the sibling tools, so the guidance remains implicit rather than direct.

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 behavioral burden. It discloses non-execution ('Talon recommends, it does not fill'), non-signing, GET/POST semantics, polling cadence, and the 'not financial advice' caveat. It could add auth/rate-limit details or explain domain jargon like 'sign' and 'avoid,' but the core behavioral traits are transparent.

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?

Every sentence earns its place. The core purpose is front-loaded, followed by actionable usage and explicit limitations. The fragment style is compact and scannable while preserving meaning.

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 single-optional-parameter tool with no output schema, the description covers invocation, polling, return source, and limitations well. The main gap is that 'live target book' is not expanded with the fields an agent should expect, but the reference to calls/say and the trade recommendation role provide enough operational context.

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 baseline is 3 even without parameter detail in the tool description. The description adds context that holdings are submitted via POST to get a diff and that sizing/exits remain the caller's responsibility. It does not elaborate on individual optional fields, which is acceptable given the schema already covers them.

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 an autonomous trader for Hands that returns the live target book, and distinguishes its read endpoint (GET) from the holdings submission (POST). It is specific about resource and action, though 'autonomous trader' is immediately qualified by 'it does not fill,' which softens the label. It doesn't fully distinguish itself from the many talon_* siblings, but names calls/say as complementary resources.

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?

Explicit usage guidance is provided: poll every 5–15 minutes, POST holdings to get a diff, GET for the book only, and read calls/say for conviction. It also states exclusions—Talon does not fill, sign, or override caller sizing/exits, and says to honor avoid. This gives clear when-to-use and when-not-to-expect guidance.

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 burden and does well: it discloses the scoring methodology (volume/cap, FOMO cluster, whale hits, stock-route pairing, live LP), explains the core/early graduation distinction, and warns that early candidates have a 99% failure rate. It also frames output as research rather than actionable orders.

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 purpose. Each sentence adds relevant context, though the dense jargon (FOMO cluster, stock-route pairing, live LP) makes it less immediately scannable than it could be.

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 should clarify what the returned feed looks like, but it does not. It also leaves 'minP' undefined and does not explain the 'all' band option. An agent could call the tool with defaults, but full correct invocation with non-default parameters is under-specified.

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 0%, so the description must explain the parameters. It does explain 'band' by defining core ($200k–$1m) and early ($20k–$200k), but it never explains 'minP' or 'limit'. 'limit' is self-evident, but 'minP' is cryptic and undocumented in both schema and 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 description clearly identifies a token feed: tokens in two market-cap bands scored for a $10m potential, which is more specific than a generic 'breakout' name. It distinguishes internal modes (core vs early) but does not explicitly differentiate this from the many talon_* 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?

The description implies a research use with 'Research candidates, not orders' and explains the early band's risk profile, but it gives no explicit guidance about when to choose this tool over alternatives such as talon_alpha, talon_radar, or talon_scan. There are no when-not conditions beyond not treating output as orders.

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 provided, the description carries the burden of behavioral disclosure. It does add methodological context by mentioning on-chain Transfer logs and DEX buy-pressure heuristics, which indicates the analysis's data basis. But it does not state side effects, permissions, return format, or limitations, leaving some behavioral uncertainty.

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 compact sentence with no redundancy or filler. It front-loads the core function and adds the data sources efficiently. It is concise, though its brevity contributes to omissions in other dimensions.

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 one parameter, no output schema, and no annotations, the description is too sparse for confident invocation. It fails to clarify what 'address' refers to, what output is returned, or any behavioral expectations, leaving important context missing.

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 has one required 'address' string with 0% description coverage, and the tool description does not mention the parameter at all. The word 'address' provides only a basic hint, but it is ambiguous whether this is a token contract, a wallet, or something else, and no format or chain information is given.

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 clear topic (bundle/sniper analysis) and names the specific data sources (on-chain Transfer logs, DEX buy-pressure heuristics). It is not a tautology and gives a distinctive identity among the many similarly named talon_* siblings, though it lacks an explicit verb and does not name sibling differences.

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 when to use the tool: when bundle/sniper analysis from transfer logs and DEX heuristics is needed. However, it does not provide explicit alternative conditions or mention any sibling tools for comparison, so usage guidance is only implied, not clearly directed.

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?

No annotations are provided, so the description bears the full burden of behavioral disclosure. It lists the data domain but does not explicitly state whether the operation is read-only, whether permissions are required, or what output shape to expect. 'Checks itself' weakly implies a non-mutating lookup, but this is not clearly disclosed.

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 sentences with no filler. 'Model ledger' front-loads the core purpose, and the self-check phrase adds a useful intent signal 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?

For a zero-parameter tool with no output schema, the description provides sufficient domain content and intent to support selection and basic expectation-setting. The main omission is a precise statement of the return format, but the tool's low complexity makes this a minor gap.

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 has zero parameters, so the baseline is 4. The description adds meaningful context by enumerating the fixed content an agent can expect: open calls, settlement windows, hit/miss status, and Hedge weights. There is no parameter ambiguity to resolve.

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 identifies the tool as a 'Model ledger' and enumerates its contents: open $10m calls, 7d/30d settlements, hit/miss, and current Hedge weights. This is specific and informative, though it lacks an explicit verb like 'list' or 'view'. It still differentiates reasonably from the many sibling tools by describing a self-evaluation ledger.

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 'This is how the algorithm checks itself' provides a clear diagnostic context, implying the tool is used for reviewing model call performance and settlement status. However, it does not explicitly state when to use this tool versus alternatives or when not to use it, leaving some inference required.

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 provided, the description carries the full behavioral burden, but it only lists data content. It does not disclose the time-window behavior implied by the `window` parameter, what 'tracked FOMO traders' means as a filter, whether the result is a record list or an aggregate summary, or any read-only/data-freshness 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?

The single colon-delimited phrase is compact and front-loaded, with zero wasted words. But it reads more like a dashboard subtitle than a tool definition — the brevity crosses from disciplined conciseness into under-specification, omitting action and controls.

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 no annotations and no output schema, the description must explain parameter effects and return shape; it does neither. The field list (cost, proceeds, P/L, hold time, win/loss) gives partial credit on return content, but the window/limit semantics and the structure of a 'round-trip' record are missing.

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 0% and the description never mentions `limit` or `window`. The enum values make `window` plausibly a look-back range, but `limit`'s semantics (presumably a cap on returned round-trips) are pure guesswork, and the interaction between the two parameters is entirely unexplained.

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 specifies a concrete data domain — closed round-trips for tracked FOMO traders — and enumerates the returned metrics (cost, proceeds, P/L, hold time, win/loss). However, it contains no action verb, so whether the tool lists trades, computes aggregates, or exports data is left to inference. It also makes no attempt to distinguish itself from the ~40 siblings, several of which (talon_calls, talon_winners, talon_traders) plausibly overlap.

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, no exclusions, and no reference to any alternative among the sibling tools. An agent choosing between talon_closed and talon_winners, talon_calls, or talon_flow receives no basis for the decision.

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 behavioral disclosure burden, and it does disclose important traits: Talon does not sign, output is not a fill size or an exit, and it defines 'clustered' behavior. This is valuable safety-relevant context. It omits return-format details and does not explicitly say read-only, but the non-signing disclaimer substantially covers the main risk.

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 extremely compact and front-loads the core metaphor and criteria before moving to categories and exclusions. There is no filler. The telegraphic, fragment-heavy style ('smart vs sniper', 'Not a fill size. Not an exit.') slightly hurts readability, but every phrase earns its place.

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 tool, the description covers the core concept well and includes important disclaimers. However, it never explicitly states what the output looks like (e.g., a list of wallets with labels), and it leaves '7-figure name', 'smart', 'sniper', and 'desk' undefined. The absence of an output schema makes these gaps more significant.

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 input schema is empty and there is nothing to clarify. The description instead explains the tool's conceptual output categories ('smart vs sniper', 'clustered'), which is the relevant semantic content. Baseline 4 applies for zero-parameter tools.

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 gives a recognizable metaphor ('Nansen for this chain') and specific cohort criteria ('Wallets that bought a 7-figure name under $200k'), which implies an analytics tool that identifies wallet groups. However, it lacks an explicit operation verb like 'returns', 'lists', or 'identifies', and key terms such as '7-figure name', 'smart', and 'sniper' are undefined. It does not clearly distinguish itself from the many talon_* sibling tools beyond cryptic exclusion phrases.

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 meaningful negative guidance: 'Not a fill size. Not an exit. Talon does not sign.' tells an agent this tool is not for execution, fills, or exits. 'Snipers do not fire the desk' gives a pipeline-specific exclusion. It stops short of naming alternative tools or stating a positive 'use this when...' condition, so it misses the top score.

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 of behavioral disclosure, but it mostly provides domain context rather than execution behavior. It explains what routingVolume24h measures but does not state what the tool returns, how sorting behaves, whether results are live, or any side effects. This leaves significant ambiguity for an agent deciding whether to call it.

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-loads the core purpose. The parenthetical definition of routingVolume24h is useful context, though the phrase 'the hop meme trades take' is cryptic and slightly detracts from clarity. Overall, it is efficient and avoids unnecessary 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?

The tool has no output schema, no annotations, and sparse parameter documentation, so the description needed to provide more operational context. It does not describe the response shape, the default sort behavior, or how limit interacts with the result set. An agent would still be uncertain about what this tool actually returns.

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 0%, so the description must compensate for parameter meaning. It does add value by defining routingVolume24h, which maps to the 'routing' sort option, and 'Hottest' hints at a ranking. However, it does not explain 'memes' or 'tvl' sort values, nor does it mention the limit parameter's practical effect.

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 identifies a specific resource—'tokenized-stock complexes on Robinhood Chain'—and conveys a ranking intent with 'Hottest.' It also defines the key metric routingVolume24h, which helps distinguish this tool from siblings like talon_hot. However, it lacks an explicit verb such as 'list' or 'return,' so the action is implied rather than stated.

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 gives no guidance about when to prefer this tool over the many talon_* siblings. It implies a use case (finding hot stock complexes) but does not mention alternatives, exclusions, or conditions. An agent would have to infer selection from the resource name alone.

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 present, the description carries the behavioral burden. It usefully discloses that the data is live, refreshed every 1 second, and that the tool is not a signed order, implying read-only data access without order side effects. It does not mention pagination, rate limits, or authentication, but the core behavioral traits are clearly surfaced.

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 short and front-loaded with the main purpose, and each sentence contributes distinct information. Some phrasing is cryptic, such as 'Plug a table on /data anytime' and 'Not a signed order,' which slightly reduces clarity but does not make the description bloated.

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 simple three-parameter, read-only data tool, the description provides the essential context: source, freshness, snapshot/slice mode, and a side-effect caveat. However, without an output schema it does not fully define the response shape, and the effect of `limit` and `window` on the returned data is left implicit.

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 phrase 'Board snapshot ... or a slice' adds meaning to the `slice` parameter, and listing board fields helps an agent understand the returned shape. However, schema description coverage is 0%, and `limit` and `window` are not explained beyond their names and enum values, so the description only partially compensates for the missing 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 clearly identifies the tool as a fast datasource for live robinhoodtrenches.com trades, with 1-second freshness and board-snapshot or slice retrieval. It distinguishes itself from an order tool with 'Not a signed order,' but it lacks an explicit action verb like 'get' or 'fetch' and does not clearly separate itself from the many sibling talon_* analysis 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 gives clear context for when to use the tool: as a datasource for a UI or an agent, and for plugging into a table on /data anytime. It also provides an exclusion ('Not a signed order'), though it does not name alternative sibling tools or describe when one of those should be preferred.

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 of behavioral disclosure. It does mention some traits ('stays up for six hours', 'No fill size. No exit. Does not sign.'), but these are presented without context of the primary action. The lack of a stated fundamental behavior makes these details confusing, so transparency is incomplete.

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 paragraph of rules, not concise or well-structured. It front-loads 'High-conviction book' but then piles on a stream of conditions without clear organization. While each sentence conveys some detail, the lack of structure makes it harder to parse, though it is not excessively long.

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 no input schema, no output schema, and no annotations, the description must fully explain what the tool does and what it returns. It does neither—it only lists selection criteria. The agent cannot infer the tool's purpose or output format, so the description is incomplete.

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 and an empty schema, so the baseline is 4. The description correctly does not attempt to explain nonexistent parameters; there is nothing for it to add.

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 does not state a clear verb or action—it reads as a set of criteria for a 'high-conviction book' rather than explaining what the tool does (e.g., list, filter, monitor). It is not a tautology but is vague about the core functionality, making it hard for an agent to know what invoking this tool returns or triggers.

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?

No guidance is given on when to use this tool versus its many siblings. The description contains conditions (e.g., 'Famous desks still count when that fill is under $400k') but these are behavioral rules, not usage advice. There is no mention of alternatives or explicit when-to/when-not-to use scenarios.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not explain whether the operation is read-only, how 'newly seen' is determined, whether data is returned in a particular format, or what side effects or limits exist.

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 short, front-loaded with the core purpose, and each sentence adds value. It conveys the resource, output content, and intended use without wasted words.

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 annotations, no output schema, 0% parameter coverage, and many sibling tools, the description is too minimal. It does not cover parameter meaning, expected return shape, or how this differs from similar discovery tools like talon_radar or talon_hot.

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 0%, and the description does not explain the parameters such as maxAgeHours, minLiquidity, or limit. It only loosely ties 'newly seen' and 'confluence scores' to sort options, which is insufficient for an agent to set parameters confidently.

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 specific verb ('Detect'), a specific resource ('newly seen Robinhood Chain tokens'), and the key output content ('market stats and confluence scores'). The phrase 'newly seen' and the use case 'hunt early memes/alts' help distinguish this tool from likely siblings focused on hot or breakout tokens.

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 gives clear context: use this tool to hunt early memes/alts. However, it does not explicitly say when not to use it or name alternatives among the many talon_* siblings, so it stops short of full guidance.

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 behavioral burden. It does disclose that this is research rather than an order, which is useful, but it omits what output the agent should expect, whether it performs any writes, and what data sources or limitations apply.

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 short, front-loaded with the core subject, and every sentence adds color or constraint. The informal jargon is vivid but sacrifices a little 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?

The tool has only one parameter and no output schema, yet the description still does not say what the research result looks like or how to interpret the findings. An agent can call it with an address but not anticipate the return value.

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 already fully documents the lone 'address' parameter as a Token 0x on Robinhood Chain. The description adds no new parameter-level semantics, so the baseline score 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 identifies a specific on-chain research target: Pons tax-exempt snipe clusters and fake-activity boosts. 'Research, not an order' provides actionable verb-like framing, distinguishing it from execution 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 gives clear context: use this tool when investigating suspicious on-chain clustering and fake activity, and explicitly says not to treat it as an order. However, it does not name alternatives or state when to prefer another talon_* tool.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose that missed printers fail the build and that last-3-days is a live mode, but it says nothing about return values, side effects, or what 'the same flag' refers to.

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 only three sentences and contains relevant information, but the first sentence is a long, convoluted rhetorical question packed with price ranges and examples. Key behavioral facts are buried in the second sentence instead of being front-loaded.

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 should explain what the tool returns or what success/failure looks like, but none of that appears. Undefined terminology ('printers', 'FOMO book', 'flag') and a custom domain make the description insufficient for an agent to invoke the tool confidently.

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 and an empty input schema, parameter documentation is not needed. The description does mention a 'flag' that is not exposed in the schema, but since there are no actual parameter semantics to clarify, the baseline of 4 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 frames the tool as an evaluator of whether Talon caught certain coins, with a locked-fixture mode that fails builds on misses. However, it is phrased as a rhetorical question rather than a direct statement of action, and it relies on undefined jargon ('printers', 'FOMO book') so it is only vaguely separable from the many talon_* 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?

The description implies two usage contexts: locked fixtures as a build-time check and last-3-days as a live mode. There is no explicit 'use this when...' guidance and no comparison to sibling alternatives, so an agent can only infer when it should be chosen.

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 provided, the description must carry the behavioral disclosure burden. It only adds 'with lag in seconds' as a behavioral detail; it does not disclose whether this is read-only, what data is returned, pagination behavior, or any limitations.

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 compact sentence with no filler. It front-loads the core concept and includes the notable 'lag in seconds' detail, though the sentence is structurally incomplete as a definition.

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 should clarify what the tool returns and how to interpret the results. It defines the concept but does not explain the output shape, parameter effects, or practical usage context, leaving an agent to guess at the response format.

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 0%, and the description does not mention the limit or window parameters at all. The schema names and enums are somewhat self-explanatory, but the description adds no semantic value about how these parameters affect the returned copy-flow data.

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 identifies a specific resource and concept: copy-flow data showing a FOMO lead buy and the wallets that followed into the same token, with lag in seconds. This is reasonably distinct from the many sibling talon_* tools, though it is phrased as a noun phrase rather than a clear verb+resource 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?

The description gives no guidance on when to use this tool versus the numerous siblings such as talon_calls, talon_traders, or talon_cohort. There are no explicit contexts, exclusions, or alternative routing signals.

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?

No annotations are provided, but the description does disclose some behavioral traits: 'Not a thesis. Not a fill. Does not sign.' This tells the agent that the tool does not perform certain actions (like trading or signing), which is valuable. However, it does not explain what it does do (e.g., does it return data? Does it require authentication? Does it have side effects?). The phrase 'Does not sign' is cryptic without 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 short but not well-structured. It is a fragmented, noun-phrase-heavy text that reads like a stream of consciousness. It is not front-loaded with the main purpose; instead, it starts with a URL and cryptic terms. Every sentence is cryptic, making it hard to parse quickly.

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 that there is no output schema and no annotations, the description is the only source of information, and it is insufficient. It does not explain what the tool returns, how it works, or what the user should expect. The jargon ('Bursts', 'Fresh', 'Exits') is undefined. For a tool with zero parameters, it might be acceptable to be abstract, but the description is too vague to be actionable.

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 no parameters, and the schema coverage is 100% (trivially). With zero parameters, the baseline is 4. The description does not need to explain parameters, but it also does not explain what inputs the tool expects, since there are none. The description is somewhat self-contained.

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 is cryptic and does not state a clear verb-resource pair. It mentions 'fomoradar.app' and 'Real wallets behind fomo.family handles, scored' but does not explain what the tool actually does (e.g., 'Get scoring analysis for wallets'). The mention of 'Bursts', 'Fresh', 'Exits' adds jargon without clarifying the tool's purpose. It does not distinguish from siblings like talon_radar.

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 alternatives. It does not mention use cases, conditions, or alternatives. The description is purely explanatory of internal concepts, not actionable usage.

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 behavioral burden, and it does so meaningfully: 'Does not sign' states that this tool does not execute transactions, and the hint about slice-of-supply tells the agent that output is advisory rather than directive. It doesn't cover every possible side-effect or return detail, but the key behavioral limitations are disclosed.

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 short sentences, each earning its place: what the tool returns, how to interpret it, and what it does not do. The subject is front-loaded and there is no 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?

The description explains the tool's scope and key caveats well, but it leaves minP undefined and provides no explicit return structure beyond the suggested slice. Since there is no output schema or annotations, these omissions are meaningful gaps.

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 0% and the description never mentions minP or limit. minP is particularly opaque despite its default/min/max constraints, so an agent cannot determine what it controls or how to set it correctly.

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 resource and scope: just-graduated Pons coins under $200k. It lacks an explicit verb like 'lists' or 'returns' and doesn't call out sibling screeners, but the core purpose is specific and understandable.

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 clear usage context: use it for newly graduated low-cap coins, and it directs the agent to talon_calls for conviction levels. It also sets expectations with 'Suggested slice of supply is a hint' and 'Does not sign', which function as when-not guidance, though it doesn't enumerate all alternative tools.

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 must disclose behavior itself. It does provide some constraints: 'Does not sell. Does not sign.' and 'Health, story, scan, and diligence are already on each buy.' It also mentions routing ('Solana fills on Jupiter') and time windows ('First twenty minutes'). However, these are buried in strategy details and not clearly attributed to the tool's own behavior, so the disclosure is incomplete and hard to parse.

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 long, unstructured block of trading instructions, mixing strategy, execution rules, and warnings. It lacks clear sections, front-loading, or a concise summary of the tool's function. Nearly every sentence is verbose and redundant, making it difficult for an agent to extract key information quickly.

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 has no annotations and no output schema, the description is the sole source of context. It fails to explain what the tool returns, what happens after invocation, or how the provided inputs (avoid, holdings) affect the execution. The focus on strategy details leaves critical operational information missing.

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 descriptions already cover both parameters: 'avoid' (addresses scan already marked avoid) and 'holdings' (what this wallet already holds). Since schema description coverage is 100%, the baseline is 3. The tool description adds no additional meaning about these parameters, so no reason to deviate.

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 reads as a trading strategy narrative rather than a tool purpose. It says 'The one Hands call' and describes a series of actions ('watch every mint', 'buy on opening volume'), but never explicitly states what the tool does as a function (e.g., executes trades, monitors mints, or returns a decision). The purpose is vague and not differentiated 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?

The only guidance is a negative instruction: 'Do not call scan, story, desk, open, wire, or diligence on the Hands loop.' This implies when not to use other tools, but it does not state when to use this tool versus alternatives, nor does it provide conditions or prerequisites for invoking it.

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 provided, the description carries the behavioral burden. It indicates this is a read-only status check and names the systems covered, but it does not describe what happens if an upstream service is down, whether remote calls are made, or what the output looks like.

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 sentence that front-loads the action and purpose, then efficiently enumerates the upstream components checked. Every word earns its place and there is no 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?

For a zero-parameter health-check tool, the description provides the essential context: what is checked, the specific upstream services, and when to run it. It lacks an explicit description of return values or failure behavior, but the simplicity and narrow scope make this a minor gap.

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, and the schema already fully covers this with an empty properties object. The 0-parameter baseline of 4 applies, and the description adds useful context about the tool's purpose even though there are no parameters to explain.

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 verb 'Check' and the resource 'Talon and upstream status,' enumerating specific upstream services. This distinguishes it from sibling tools, though it does not explicitly contrast itself with any sibling.

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 'before a research run' gives explicit timing for when to invoke this tool. It does not name alternative tools or state when not to use it, but the intended context 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?

With no annotations, the description carries the full disclosure burden. It discloses that results are ranked by clustered dollar flow and clarifies the behavioral meaning of autobuy, including exclusions for stocks and single-sniper prints. It does not mention response format or rate limits, but the key operational caveats are present.

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 tight and front-loaded: it states what is hot and how it is ranked in the first clause, then adds the autobuy caveat in a separate sentence. Every sentence earns its place, and there is no filler or repeated schema information.

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?

This is a low-complexity tool with only two optional, self-describing parameters and no output schema. The description explains the output concept, the ranking method, and a critical behavioral caveat about autobuy. It does not enumerate exact output fields, but that is not necessary for this simple read-style 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 description coverage is 0%, and the description does not mention limit or window at all. The schema provides defaults and enums, but the description adds no parameter-level meaning, so it fails to compensate for the lack of schema descriptions. The only implicit temporal hint is 'right now'.

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 clear purpose: surface tokens that tracked FOMO wallets are buying right now, ranked by clustered dollar flow. This names the resource and ranking basis, which distinguishes it from generic talon_* siblings. It does not explicitly name a sibling alternative, so it stops short of a 5.

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 gives operational cautions: autobuy=true is a recommendation, not a fill size, and stocks/single-sniper prints stay off autobuy. This is useful context but does not explicitly say when to prefer talon_hot over similar tools like talon_flow or talon_wallet. The usage guidance is implied rather than fully specified.

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 behavioral burden. It discloses that the API key is shown only once, must be sent as X-Talon-Key, usage is counted, and there is no seat fee. It doesn't cover repeated-call behavior or key recovery, but the one-time display instruction mitigates the main risk.

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?

Each short sentence earns its place: purpose, human-free process, key behavior, auth header, usage policy, and call timing. No filler, repetition, or irrelevant 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?

For a low-complexity signup tool with no required parameters, the description fully covers the essential context: what it does, when to call it, what to do with the key, and the business implications. The schema fills in the optional parameter details, so nothing critical is missing.

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 already describes name and webhook, and role is self-explanatory via its enum and default. The description adds no parameter-level meaning, but none is critically missing because schema coverage is 67% and the uncovered parameter is a simple enum.

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 specific verb and resource: 'Agent self-serve signup' and 'Mints an API key'. It explicitly frames this as the first-time onboarding call, which clearly distinguishes it from the many sibling tools that appear to be feature or data 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 gives a clear usage trigger: 'Call this the first time you land here.' It also implies no human involvement is needed. It doesn't explicitly name alternatives or exclusions, but the first-time prompt is sufficient given the sibling list.

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 behavioral burden. It discloses key ranking behavior and criteria, and 'Rank' implies a read-only operation. However, it does not describe output shape, whether the tool auto-filters or merely suggests filters, or what the final 'Do not LP the meme' instruction means functionally.

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 very compact, with the core purpose front-loaded and each phrase adding selection-relevant information. No filler or redundant restatement of the tool name exists.

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 is enough for basic invocation and parameter selection, but there are real gaps: no output schema means return values are unexplained, 'official' and 'meme' are undefined, and limit/minAgeHours are not addressed. For a 7-parameter tool with no annotations, this is 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?

Schema description coverage is 0%, so the description must add meaning, and it does for several parameters: quote maps to USDG/WETH, protocol/hooks map to v3/no hooks, minTvl maps to the $100k threshold, and the preferred sort theme is given. It does not explain limit or minAgeHours, and 'volume/TVL' is not an exact enum value, so it is not fully compensating.

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 specific verb and resource: 'Rank official stock/USDG (or stock/WETH) LP pools.' This clearly distinguishes it from generic siblings like talon_pool and gives concrete selection criteria rather than a tautology.

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 intended use case is clear: rank official stock/USDG or stock/WETH LP pools. It provides selection guidance such as preferring v3, no hooks, and a $100k TVL threshold, but does not explicitly name alternatives or define when not to use this tool versus a sibling.

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?

No annotations are present, so the description carries the burden. It discloses that the tool registers an HTTPS callback, that POSTs are event-driven, that only the last event is available via /monitor, and that there is no dashboard. It doesn't cover retries, auth, or payload shape, but for a one-parameter tool this is solid 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?

Three short sentences that front-load the purpose, then the trigger behavior, then the polling fallback. Every clause carries distinct information with no filler or repetition.

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 is sufficient for a simple one-parameter tool with no output schema: it explains how to set the webhook, when notifications occur, how to read the latest event, and why no dashboard is needed. The main gap is the response/return behavior when the webhook parameter is omitted, but the schema is small enough that this is a minor omission.

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 already documents webhook as an HTTPS callback and says an empty string clears it, giving 100% coverage. The description adds useful context by explaining that this callback is the destination for event POSTs, which goes beyond the schema's basic type 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?

States a concrete action ('set a webhook'), the triggers that cause Talon to POST (clustered buys, copied desks, dumped bag), and the alternative read path (poll /monitor). This clearly identifies it as the event-monitoring/webhook tool among the many talon_* siblings rather than a data or analysis 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?

'Long-running agents' establishes when to use it, and the webhook-vs-poll distinction gives the agent two usage modes. It doesn't name sibling alternatives or state explicit when-not conditions, but the context is clear enough without exclusions.

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 must carry the full burden. It hints at behavior like 'A real-LP sit stays six hours' and 'No exit', suggesting time-limited opportunities, but doesn't clarify permissions, reversibility, or rate limits. The phrase 'Does not sign' indicates it's a read-only or non-transactional tool, but this is vague and buried.

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 series of short, cryptic sentences that are not front-loaded with a clear purpose. While it's concise in length, the structure is disjointed, making it hard to parse. Every sentence should earn its place, but some like 'No named FOMO handle required' add ambiguity without clear benefit.

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 zero parameters, no output schema, and no annotations, the description is the sole source of information, but it's incomplete and unclear. It doesn't explain what the tool returns, the format of its output, or its exact purpose. For a tool with no structured fields, the description should be much more explicit.

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 score is 4. The description doesn't need to explain parameters, and it correctly avoids doing so. No additional value is added or needed here.

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 is written in cryptic trading jargon. 'New pools on this chain: live LP, still under $400k' hints at discovering fresh liquidity pools, but there's no clear verb like 'list', 'find', or 'open' that states the action. Sibling names like talon_scan or talon_radar suggest similar functionality, making it hard to distinguish from them.

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 explicit guidance on when to use this tool versus alternatives like talon_alpha or talon_pool. Phrases like 'Fresh dust drops after 45 min' and 'Off-chain printers live on talon_wire' imply use cases but don't state conditions clearly. No when-not-to-use or alternative tools are mentioned.

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?

No annotations are provided, so the description must carry the behavioral burden. It discloses the playbook's strategic stance—preferring concentrated liquidity on official stock/USDG pools over holding memes—but it does not state whether the tool is purely informational, what output format to expect, or any side effects. The word 'playbook' softens this gap but does not fully close it.

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 clearly identifies the playbook's theme and strategy. Every phrase adds context, with 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?

For a zero-parameter tool with no output schema, the description covers the essential selection context: LP season, meme-flow capture, and the specific pool strategy. It could be more explicit about what the tool outputs, but the resource and strategic positioning are sufficiently clear.

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 there is no parameter meaning to clarify. The baseline for a zero-parameter tool is 4, and the description does not need to compensate for missing schema 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 identifies a specific resource (LP-season playbook) and states the strategy it promotes: capturing meme flow via concentrated liquidity on official stock/USDG pools rather than holding memes. It is more informative than a bare restatement of the name, though it does not explicitly say what invoking the tool returns or performs.

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 context is implied through 'LP-season' and 'instead of holding memes,' suggesting when this playbook is relevant. However, it names no sibling tools or explicit conditions for choosing this over alternatives like talon_lp, talon_pool, or talon_stock.

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?

No annotations are provided, so the description carries the full burden. It does disclose the output contents (TVL, volume/TVL, fee APR, range hint, hook risk, verdict), and 'Inspect' suggests a non-mutating read operation. However, it does not explicitly state read-only behavior, potential failure modes, or any required preconditions.

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 concise, front-loaded sentence communicates the tool's purpose and deliverables in a clear colon-delimited list. Every word contributes value with no 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?

For a simple one-parameter tool with no output schema, the description is mostly complete: it specifies the accepted pool types, the single input, and the expected output metrics. It slightly lacks explicit notes on error handling or unsupported pool types, but overall an agent has enough context to call it correctly.

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 single 'address' parameter with 100% coverage. The description adds no additional meaning about the parameter beyond what the schema provides, 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 ('Inspect'), a clear resource ('one stock/USDG or stock/WETH pool'), and enumerates exactly what will be returned. This clearly distinguishes it from broader scan or list tools among the siblings by narrowing scope to a single pool.

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?

No explicit guidance is given on when to use this tool versus alternatives. The description implies it is for inspecting a specific pool, but it never names sibling tools or states conditions for choosing talon_pool over, for example, talon_lp or talon_scan.

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?

No annotations are provided, so the description carries the full behavioral burden. It reveals the comparison inputs and a decision rule, but it is ambiguous whether the tool only reports a premium signal or actually executes the acquisition; the imperative 'acquire' could be interpreted as an instruction to the agent or as the tool performing a trade.

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 only two short sentences, with the core comparison front-loaded and no filler. Every phrase contributes to explaining the tool's purpose or the resulting decision rule.

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 has one simple parameter, no output schema, and no annotations, so the description does most of the work. It conveys the core signal and an action rule, but it leaves undefined what output shape the agent should expect, what threshold counts as 'high', and whether the tool has side effects.

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 0%, but there is only one parameter named 'symbol'. The description's domain language ('stock', 'RHJ') weakly implies that symbol is a stock ticker, but it never explicitly defines the expected symbol format or meaning, so it only minimally compensates for the missing schema 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 description identifies a clear comparison object: AMM price versus official RHJ true bid/ask, and gives a conditional action rule. It does not use an explicit verb like 'returns' or 'calculates', and it does not name any sibling to distinguish from, so it stops short of a 5.

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 second sentence supplies a practical rule: if premium is high, acquire via Rialto (propAMM) not the AMM. This implies the tool's purpose but does not explicitly say when to invoke this tool versus other talon_* tools, nor define what 'high' means.

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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It hints at recency and early-stage tokens but never states what the tool actually returns, how results are ordered, what data source it scans, or whether it is read-only. The behavioral contract is significantly underspecified.

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 sentences with no filler. The core value proposition is front-loaded and the phrasing is memorable and efficient, making it easy to parse at a glance.

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 annotations, no output schema, and no parameter explanation, the description leaves too much unspecified. An agent would not know what the result looks like, how to tune limit or minutes, what 'FOMO wallets' means operationally, or how this relates to sibling tools. The definition is evocative but not complete enough for reliable 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 description coverage is 0%, so the description must compensate for the two parameters, limit and minutes. It does not explain either parameter, though 'just touched' loosely aligns with the idea of a recency window. The description adds minimal semantic value beyond the parameter names.

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 conveys a specific screening purpose: surfacing fresh tokens recently touched by FOMO wallets, with the goal of catching early 'prints.' This is more than a tautology and gives an agent a basic idea of the tool's niche, though it does not explicitly differentiate it from many similar-looking siblings like talon_hot, talon_breakout, or talon_signals.

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 'Use to catch first prints before they crowd' provides some usage context, implying it should be used for early detection ahead of a crowd. However, it does not specify when not to use it, nor does it mention any alternative tools or conditions that would make another sibling more appropriate.

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 provided, the description carries the full behavioral burden, and it does disclose meaningful safety traits: 'Research, not an order' and 'Talon does not sign' tell the agent this tool has no execution authority, and 'POST trains. GET scores' reveals method-dependent behavior. However, it is silent on side effects of training (does it overwrite the existing policy? persist state?), which is a notable gap for a mutation-capable 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?

Six short sentences, zero filler, and the core resource is front-loaded. Every sentence earns its place: training source, train/score behavior, copy threshold, and safety disclaimers. The flow is slightly disjointed (jumps from training data to HTTP behavior to threshold to disclaimer), but nothing is wasted and it remains compact.

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 should define what GET returns, but pCopy is referenced ('Copy when pCopy>=0.5') without ever being specified as the response field or a computed score. It also doesn't say what happens upon successful training, whether training overwrites prior state, or what failure looks like. The safety context is well covered, but the functional contract has real gaps for a dual-mode train/score 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 description coverage is 100%, so the single 'train' parameter is already fully documented in the schema. The description's 'POST trains' merely echoes the schema's 'Default false on GET, true on POST' without adding new parameter-level detail. The description gives no extra meaning about the parameter beyond what the schema already provides, 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 identifies a specific resource (PufferLib policy trained on settled trades of frankdegods and the live FOMO board) and the two actions (train, score), so an agent can roughly tell what it does. However, the actions are expressed indirectly through HTTP-method shorthand ('POST trains. GET scores live names.') rather than a direct verb+resource statement, and domain jargon (pCopy, FOMO board) is left undefined. It doesn't explicitly differentiate from any 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?

There is no guidance about when to select this tool versus any of the 40+ talon_* siblings, and no alternatives are named. The 'Copy when pCopy>=0.5' line is a trading decision rule rather than tool-selection guidance. The only implied context is that POST vs GET selects train vs score, which is HTTP-method behavior, not a usage guideline.

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 of behavioral disclosure. It mentions the check type and data sources, but does not state whether the operation is read-only, what it returns, whether external API calls are made, or any side effects. 'Check' implies non-mutating, but this is not explicit.

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 that front-loads the key purpose and method. Every word adds relevant context, with no filler or redundant restatement of the tool name.

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 has no output schema and no annotations, so the description needs to explain what the caller should expect. It does not describe the return format, result granularity, or limitations. For a one-parameter tool this is still a meaningful gap.

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 0%, so the description must compensate. It does partially by clarifying that the address parameter is a Robinhood Chain token address. However, it does not explain expected format, chain details, or whether the address should be a contract address.

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 specific operation: a rug/honeypot/tax/ownership check for a Robinhood Chain token. It also names the method (GoPlus plus LP heuristics), which gives the tool a distinct identity, though it does not explicitly distinguish itself from sibling tools like talon_lp or talon_scan.

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 usage context is implied: an agent can infer this tool is for token safety/rug checks on Robinhood Chain. However, there is no explicit guidance about when to use it versus alternatives, nor any conditions or exclusions.

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 burden; 'intel' and 'rug check' imply a non-mutating analysis, and 'confluence' hints at how results combine. It does not explain output shape, failure modes, or costs, though the brief parameter hints at quota awareness in the schema.

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 covers purpose, scope, and the required-use gate with zero filler. The colon list is dense but readable.

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 multi-dimensional scan with no output schema, it names the intelligence categories and positions the tool as a mandatory pre-thesis step. It could add the return format or an explicit 'use for combined analysis; use siblings for single dimensions,' but the core calling context is present.

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 adds no parameter-level detail beyond implying 'address' refers to the token to scan. 'brief' is left to the schema, which already documents it.

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?

Describes the tool as 'Full token intel' and enumerates concrete dimensions (market, rug check, bundle/sniper analysis, social signals, confluence), which distinguishes it from narrower sibling scanners. It lacks a strong verb and specific return description, but the resource and scope are clear.

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?

States an explicit condition: 'Required before any thesis on a specific token,' telling the agent when this scan must run. It does not name alternatives or exclusions, but the mandatory precondition is a clear usage hook.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Search' implies a read-only operation, but the description does not mention result shape, pagination, rate limits, or any other behavioral traits. It is not misleading, but it is minimal.

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, focused sentence with no filler. The action and target resource are front-loaded, and the search dimensions are stated compactly.

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 two-parameter search tool, the description plus input schema provides enough to invoke it correctly. However, with no output schema and no guidance about alternative tools, it omits what the response looks like and does not help an agent navigate the large sibling set.

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 description adds important meaning to the 'q' parameter by specifying that it can be a ticker, name, or narrative keyword. The 'limit' parameter is not described, but its schema constraints (default, minimum, maximum) make it self-explanatory. Overall, the description partially compensates for the 0% schema description coverage.

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 specific verb ('Search'), a specific resource ('Robinhood Chain pairs'), and the search dimensions ('ticker, name, or narrative keyword'). It does not explicitly differentiate from sibling tools like talon_scan or talon_stock, but the unique resource target makes the tool's purpose clear.

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?

No guidance is provided about when to use this tool versus the many talon_* siblings, nor are any alternatives or exclusions mentioned. Usage is only implied: use it when you need to search Robinhood Chain pairs by keyword.

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 provided, the description carries the full burden of behavioral disclosure, but it only says 'Map ... to a token.' It does not clarify whether this is a read-only lookup, what the output looks like, whether it fetches live data, or whether any side effects occur. The description is not misleading, but it is too sparse to provide adequate transparency.

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, focused sentence that front-loads the core operation and immediately enumerates the key signal categories. There is no filler, repetition, or unnecessary detail, so the structure earns a high score.

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 single-parameter data-lookup tool with no output schema and no annotations, the description is minimally viable: it tells the agent what data sources are involved and that the result is mapped to a token. However, it omits return format, address format, and the distinction between this and similar sibling tools, leaving meaningful gaps for an agent trying to use the result correctly.

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 has one required string parameter named 'address' with 0% schema description coverage. The tool description does not explain what format the address should take, which blockchain it refers to, or how it relates to the token mapping. 'Address' is somewhat self-explanatory, but the description adds no semantic detail to compensate for the empty 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 states a clear operation ('Map') and a specific resource (a token), and enumerates the signal types (X/Telegram/web, DexScreener boosts, paid profiles, community takeovers). This gives the agent a solid sense of what the tool does. It does not explicitly distinguish it from siblings like talon_social, but the enumerated sources and 'signals' framing are sufficiently distinctive.

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 offers no guidance on when to use this tool versus alternatives such as talon_social or talon_scan. There is no stated prerequisite, no comparison to siblings, and no mention of what kind of token address is expected. The usage context is only implied by the description's content, not explicitly communicated.

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 behavioral disclosure burden. It adds useful context about data provenance: live Robinhood Chain token profiles, X handles, and matching to on-chain activity. However, it does not state whether the operation is read-only, what output shape to expect, or any freshness/rate-limit caveats.

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 compact sentence with the core concept front-loaded and no filler. It conveys source, match logic, and scope efficiently, though it is slightly jargon-heavy.

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 does not explain what the returned data looks like, how limit affects results, or what 'on-chain activity' means in practice. For a tool with one parameter and many siblings, this leaves important context missing.

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, limit, has schema constraints (default 30, min 1, max 50) but the description never mentions it. With 0% schema description coverage, the description should compensate, but it adds no semantic meaning for the parameter.

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's output domain: a cross-token social graph linking X handles from live Robinhood Chain token profiles to on-chain activity. It is specific enough to distinguish from many sibling tools, though it lacks an explicit imperative verb such as 'Get' or 'List'.

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 many talon_* siblings, nor any exclusions or alternative tool references. The description only implies it is for social-graph data, leaving the agent to infer selection criteria.

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?

This is a no-annotation tool, so the description carries the full disclosure burden. It usefully states persistence behavior ('Stays on the book until they leave the band') and explicitly rules out execution actions ('No fill size. No exit. Does not sign.'), which helps an agent treat it as informational. It does not mention data source or update cadence, but the non-execution clarity is valuable.

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 short sentences front-load the key criteria and contain no filler. Some jargon ('BONER/MEME', 'on the book') hurts immediate parseability, but the length is appropriate.

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 zero parameters and no output schema, the description should at least state what calling the tool returns or emits, but it never does. The agent is left unsure whether this produces a list, a signal, or a status, and the unexplained jargon adds further ambiguity.

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 has zero properties and schema description coverage is 100%, so there are no parameter semantics for the description to add. The 0-parameter baseline 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 gives specific selection criteria ($25k–$200k, 12+ hours, live LP) and labels this the BONER/MEME sit, so the subject matter is clear. However, it never states an explicit verb such as 'lists', 'finds', or 'monitors', leaving what the tool actually does ambiguous.

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 criteria and 'Stays on the book until they leave the band' imply this is meant as a live watchlist for stalled meme coins, but there is no explicit statement about when to choose it over sibling tools or when not to use it. Usage is inferable rather than directly instructed.

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?

No annotations are provided, so the description must carry the behavioral disclosure burden. It lists output content categories but does not state whether the call is read-only, whether it returns current or historical data, how it validates input, or what the response structure looks like.

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-loads the core resource identity. It uses a scannable list of data categories with no filler, though it is telegraphic and lacks a complete sentence structure.

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 single-parameter tool, the schema and description together cover the input and the general content areas. However, with no output schema, no annotations, and no sibling-routing guidance, the description is only minimally sufficient for an agent to select and invoke it correctly in a crowded toolset.

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 covers the single parameter fully, including an example ticker and the alternative of a 0x address. The description adds no additional parameter semantics beyond what the schema already provides, 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 identifies the resource as 'One official RHJ stock token' and enumerates the data aspects it covers: bid/ask vs AMM premium, stock/USDG LP pools, meme legs, and correlated/bridge pairs. The purpose is inferable, but there is no explicit verb such as 'get', 'query', or 'analyze', and it does not explicitly differentiate from siblings beyond naming the resource.

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?

No guidance is provided about when to use this tool versus alternatives. With 40 sibling tools all sharing the talon_ prefix, an agent cannot tell whether talon_stock, talon_lp, talon_premium, or talon_data is the right choice without additional 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?

With no annotations provided, the description must carry the full burden. It mentions it is 'Fast' and implies it returns narrative text, but it does not disclose specifics like auth requirements, potential side effects, or failure modes. It also warns that a Dex handle is not a thesis, which hints at input limitations, but overall it lacks thorough behavioral disclosure.

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 concise and front-loaded with the core purpose. It includes a few imperative fragments ('Fast. Desk/open/wire already stamp a cached story.') that add value but could be more structured. Overall, it is efficient with no redundant text.

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 lack of annotations and output schema, and four parameters with zero schema coverage, the description does not provide enough context for full correct invocation. It omits the return format, error conditions, and the role of non-required parameters, making it insufficient for an agent to confidently use it in all scenarios.

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 0%, so the description must explain parameters. It only indirectly clarifies that 'symbol' is the named ticker (via 'Use this for a named ticker') and implies the tool fetches narrative for that ticker. The other parameters (name, address, quoteSymbol) are not explained at all, leaving significant ambiguity in how they affect the tool's behavior.

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 purpose: it provides the narrative for a new token, including the tweet or site thesis and purchaser info. It distinguishes itself from siblings by warning 'A Dex handle is not a thesis' and noting that 'Desk/open/wire already stamp a cached story,' clarifying this is for fresh narratives on named tickers.

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 usage guidance: 'Use this for a named ticker' and implies that desk/open/wire should be used for cached stories. It also warns against using a Dex handle as a thesis. However, it does not enumerate all alternatives or explicitly state when not to use it beyond the cached story caveat, so it's good but not exhaustive.

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 provided, the description carries the full burden and does substantial work: it discloses that the desk is live and not fixed, that anyone with fills or closed trades receives a weight, that named handles are aliases, and that data comes from a fan-in of live trades, DexScreener, Robinhood chain, and X socials. It also flags 'autobuy names' as what the wallet copies, which is useful 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 compact and front-loaded with the core concept, then adds aliases, weighting, data sources, and a caveat. Each sentence adds information, though the 'Not financial advice' boilerplate is conventional rather than functional and the jargon is 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?

Given there are no parameters and no output schema, the description gives a reasonably complete picture of what the tool represents: a live, weighted, multi-source desk with alias handling. It could be more explicit about the exact shape of the returned data, but for a zero-parameter live-view tool it provides enough context for an agent to select and invoke it.

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 accepts zero parameters and the empty input schema fully captures this. The description's job is therefore not to explain parameters, but to explain what the parameterless tool returns, which it does.

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 identifies the tool as a 'live desk' of currently profitable FOMO traders, with named handles as aliases and weights based on fills or closed trades. It does not use an explicit verb like 'returns' or 'lists', and relies on insider jargon, but the resource and scope are specific enough to distinguish it from a vague catch-all.

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 when to use the tool: when you want the current, dynamically weighted set of active printers rather than a fixed eight. However, it does not explicitly state alternatives, exclusions, or when not to use this tool, leaving the routing decision mostly to inference.

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?

No annotations are provided, so the description carries the transparency burden. It discloses that the tool returns live/recent buys and sells with an optional first-buy filter, but it omits output shape, sorting, pagination, and whether any side effects exist. This is adequate 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 compact and free of filler; each phrase contributes source, content, or filter behavior. It could be more polished as full sentences, but it is appropriately sized.

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 annotations and no output schema, the description must carry more weight. It leaves two of three parameters undocumented ('limit', 'stocks') and provides no return-format or pagination details, making it incomplete for confident 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 description coverage is 0%, and the description only explains 'first' ('keeps only first-buys'). The 'limit' and 'stocks' parameters are left undocumented, forcing the agent to infer their meaning from the schema alone.

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 states the data source (tracked wallets) and content (live trades, newest buys/sells), so an agent can identify the resource. However, it lacks an explicit verb like 'get' or 'return' and does not differentiate it from siblings such as talon_wallet or talon_calls.

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 'Live trades from tracked wallets' implies when to use the tool, and 'first=true keeps only first-buys' gives a narrowing rule. But it does not explicitly explain when to prefer this over alternatives or provide exclusion criteria, so usage guidance is mostly implied.

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?

There are no annotations, so the description carries the behavioral burden. It communicates that the tool returns a set of tracking metrics (hit rate, P/L, open bags, round-trips), implying a read-only analytics lookup. However, it does not disclose response structure, error behavior, or whether results are snapshots or historical, leaving meaningful 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 sentences with the core result set front-loaded and the input requirement immediately after. There is no filler, 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?

For a low-complexity two-parameter lookup, the description provides enough to attempt a call, but with no output schema, no annotations, and no differentiation from the many talon_* siblings, an agent may still be unsure about expected response format and when to prefer this tool. It is 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?

Schema description coverage is only 50%: the handle property is described, while window only has an enum and default. The description mostly restates the handle constraint ('fomo.family handle or 0x wallet') and is completely silent on the window parameter, so it adds little semantic value 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 identifies this as a per-trader stats lookup ('One FOMO trader') and enumerates the returned metrics (hit rate, closed P/L, open bags, recent round-trips), so an agent can tell it apart from broader or list-oriented tools. It lacks an explicit verb like 'get/fetch' and doesn't reference sibling tools, so it stops short of a 5.

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 input guidance ('Pass a fomo.family handle or a 0x wallet') but no conditions for when to choose this over siblings such as talon_traders, talon_wallet, or talon_closed. It does not mention alternatives, exclusions, or context that would guide tool selection.

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 must carry the behavioral disclosure. It does disclose the returned content categories and sortable metrics, which is useful. However, it does not describe ordering defaults, the meaning of the 'stocks' flag, whether results are aggregated or per-wallet, pagination, or any side effects or limitations.

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 sentence conveys both the resource's content and its sort options, with the core identity front-loaded. It is compact and wastes no words, though it relies on a noun-phrase style rather than a verb-led action statement.

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 4 parameters, no annotations, and no output schema, the description should provide more context: what 'stocks' controls, what window does, what the result shape looks like, and how this leaderboard differs from similar talon tools. The current text gives a good high-level summary but leaves too many operational details unstated.

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 description adds meaning to the sort parameter by explicitly enumerating valid values and indicates the domain of the data, compensating somewhat for 0% schema description coverage. But it leaves limit, stocks, and window semantics to inference from names and defaults, which is incomplete for an agent.

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 leaderboard for FOMO traders and lists the metrics it exposes (hit rate, P/L, volume, open bags), so an agent can tell what resource is involved. It lacks an explicit retrieval verb and does not contrast with closely named siblings like talon_trader or talon_wallet, so it falls short of a 5.

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 choose this tool over the many sibling talon_* tools, no mention of exclusions, and no alternative names. The description simply states what it provides, leaving the selection criteria to the agent.

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 behavioral disclosure burden. It adds meaningful traits: yield is earned via 'live Kamino + optional trade sleeve,' redemptions occur at NAV, and critically, 'Talon never signs.' It also includes disclaimers about issuance and financial advice. It could explain custody or side effects further, but it does substantial work beyond the schema.

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: concept, actions, concrete usage, trust signal, then disclaimers. Nearly every sentence adds useful context. The legal disclaimers are boilerplate but not harmful. It earns a high score for efficiency.

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 covers only the mint/redeem/hold flows. It omits the 'view' and 'mark' actions, does not explain risk parameter semantics, and says nothing about expected return values or owner default behavior. For a tool with 6 parameters and multiple enum actions, this is incomplete for agents needing to use non-default flows.

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 description adds meaning beyond the schema by connecting action=mint with usd and redemption with NAV. However, it does not clarify the semantics of the risk enum or the 'mark' action / pnlUsd relationship, leaving parts of the schema's gaps unaddressed. The schema already documents usd, usac, owner, and pnlUsd, so the added value is moderate.

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 USAC as the resource and states the core verbs: mint, hold, and redeem. The concrete instruction 'POST action=mint with usd' makes the purpose and primary call pattern unambiguous. It does not explicitly distinguish itself from sibling tools, but the resource and actions are specific enough to avoid confusion.

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 clear usage context: mint by supplying USD, hold to earn yield, and redeem at NAV. It also provides a concrete invocation pattern. However, it does not explicitly mention when not to use the tool or compare it with the many sibling tools, so it misses the top score.

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 must carry the behavioral disclosure burden, and it does add important context: 'Talon never signs' is a meaningful safety boundary, and 'POST sells so it can watch dumps' signals a side effect. It is less clear whether 'cross-chain trades' are executed or proposed, but the key behavioral caveat is present.

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 short and front-loaded with 'Smart wallet operator,' which is good. However, it is a dense, jargon-heavy run-on referencing Kamino, ghost-bags, RHJ, and dumps without defining these terms, and 'Not financial advice' adds little operational value. It is compact but not optimally structured for an AI 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?

For a five-parameter tool with no output schema and no annotations, the description is adequate but incomplete. It provides a useful safety cue and the parameter schema fills in some gaps, but it never states what the tool returns, what a minimal valid invocation looks like, or whether any parameters are effectively required in practice.

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 80%, so the schema already does most of the parameter documentation work. The schema descriptions for sells and watch are specific, and risk is described by its enum and default. The tool description only loosely echoes these concepts and adds no additional syntax, formatting, or parameter relationship details 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 labels the tool a 'smart wallet operator' and lists behaviors such as auto-save, ghost-bag radar, cross-chain trades, and an off-crypto sleeve, so the domain is identifiable. However, it never states a precise action or result of invoking the tool, and the wording reads more like feature marketing than a clear operation contract. It also does not distinguish itself from the many talon_* sibling 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?

There is no explicit statement of when to use talon_wallet versus alternatives like talon_trader or talon_calls. 'Smart wallet operator' implies wallet-level use, but the description provides no prerequisites, exclusions, or routing guidance, which is a real gap given the large sibling list.

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 is the only source of behavioral context. It communicates that the tool reports on last month's top performers, current analogs, and model takeaways, which is substantive, but it does not clarify whether this is a static report, how results are derived, or any limitations of the data.

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 brief and front-loads the core concept ('Last-month FOMO printers and live analogs') before listing examples. It is not overly long, though the dense ticker list and jargon slightly reduce 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?

For a parameterless tool, invocation is trivial and no output schema exists to document. However, the absence of usage guidance and explicit purpose leaves an agent to infer when this tool is the right one among 40+ siblings, which is the main completeness gap.

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 has zero parameters, so there is nothing for the description to document about inputs. The description still adds value by explaining the content scope, which is all an agent can ask for in a parameterless tool.

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 conveys the subject matter—last-month FOMO printers and live analogs—with concrete tickers and a mention of what the model learned, but it contains no verb such as 'lists' or 'returns,' so the exact operation remains implicit. It also does not differentiate this from the many talon_* siblings beyond the name.

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 choose talon_winners over talon_hot, talon_radar, talon_signals, or other siblings. The content hints at a retrospective winners report, but no explicit when/when-not conditions or alternatives are 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 description discloses negative behaviors ('No fill size. No exit. Does not sign.') but is silent on what the tool actually does, its side effects, or its read/write nature. With no annotations provided, the description carries the full burden and fails to explain whether this is a read-only signal or triggers any action.

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 short but dense with jargon ('six-hour keep', 'mint with the LP'). It front-loads the subject but then wanders into unclear clauses. It's not efficiently structured; the cryptic language reduces clarity more than 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 the tool's apparent complexity (crypto trading signals across chains), the description is severely under-specified. It doesn't define key terms, doesn't explain what the tool returns (no output schema), and leaves the agent guessing about the exact purpose and behavior. With no output schema and zero annotations, the description is the only guide and it's inadequate.

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 schema is trivially complete. The description doesn't need to explain any parameters, and it doesn't. This baseline score of 4 is appropriate since there's nothing to compensate for.

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 subject ('Printers on other chains') but never states the actual action the tool performs (e.g., lists, monitors, alerts). It offers cryptic distinctions and examples that assume deep domain knowledge, so an agent cannot infer what invoking this tool accomplishes.

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 references sibling tools ('Hands does not buy these', 'talon_open fires') but never gives clear when-to-use/when-not-to-use guidance. The exclusions are implied rather than explicit, and there's no statement of the conditions under which an agent should call this tool versus alternatives.

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