AstroWay Numerology

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds that it returns a 'plain-text human-readable summary' and clarifies the budget-checking purpose, providing useful context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three efficient sentences: purpose, usage guidance, and return format. Front-loaded with key information, no 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?

Despite lacking an output schema, the description specifies the return format (plain-text human-readable summary). For a simple status check tool, this is complete and sufficient.

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?

Tool has zero parameters, so schema coverage is 100%. Description does not need to explain parameters, and it adds value by hinting at the output format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'Check' and the resource 'API key status' with specific attributes (tier, credit balance, rate limits, monthly cycle reset). It distinguishes itself from the many sibling astrology calculation 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?

Explicitly instructs to run this tool BEFORE invoking expensive endpoints, providing credit thresholds (Tier 4+ at 100+ credits, Tier 6/7 at 500-5000 credits) to confirm budget.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description adds genuine behavioral context beyond them: executors are kept out of the vendor objects because an unexpected key causes a 400 on the vendor side, and cost is flagged as not in the public credit manifest. That is real operational value.

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?

Roughly three sentences, front-loaded with the purpose before the format and executor caveats. It is dense but each sentence carries information, though the format explanation partially duplicates the schema's own enum description.

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 an output schema present and full annotation coverage, the description need not explain return values, and it appropriately focuses on the vendor-shape contract and the executors/400 gotcha. It is nearly complete, with the only gap being sibling disambiguation rather than missing operational detail.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents every parameter in depth (limit ceiling rationale, select values, precision semantics). The description only restates format and its default, adding no parameter meaning the schema lacks. Baseline 3 is correct.

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 what the tool returns: tool definitions for an agent framework, generated from the live OpenAPI document. It is specific about the resource and the vendor-shape variants (openai vs anthropic objects). However, it never distinguishes this from the near-identical sibling astroway_mcp_tools_list, which an agent would plausibly confuse it with.

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 when-to-use, when-not-to-use, or alternative-naming guidance. The mention that openai objects 'spread straight into a chat completion' implies a use case, but the agent is left to infer when this endpoint is preferable to astroway_mcp_tools_list or the MCP tool-call streaming siblings.

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

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety bar is low; the description still adds real value by clarifying that endpoints are NOT invoked and that results are cached with a 5-minute TTL. It also discloses the return shape (total + per-endpoint breakdown with tier annotations), which is meaningful since no output schema exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences, front-loaded with the core capability and the non-invocation guarantee, followed by workflow guidance and the cache note. Nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no output schema, the description explains the return value, and the invocation-free and cache behaviors are covered. For a one-parameter, read-only estimator this is fully sufficient.

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% and the single 'endpoints' parameter is fully documented with examples and the leading-slash rule in the schema. The description only restates 'one or more endpoints' without adding format or constraint detail beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Estimate the credit cost of one or more endpoints') and immediately pins the scope with 'WITHOUT invoking them', which no sibling tool does. An agent can distinguish this from the many invocation/report siblings at a glance.

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?

Gives explicit workflow guidance: 'estimate first, ask user confirmation, then invoke' for multi-step planning. This is clear when-to-use context, though it names no alternative tool or when-not-to-use condition.

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

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

Annotations already declare the safe read-only/idempotent/non-destructive profile, so the bar is lowered, and the description still adds real behavioral context: the >22 digit-sum reduction rule, the centre-outward reading of the arcana chains, and the `code` format ("3-7-22") plus the shared `crossing` point. It omits cost/permission behavior, but for a pure computation tool this is solidly above baseline.

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?

Purpose is front-loaded and the two dense sentences are packed with substantive output semantics rather than filler. It is jargon-heavy and could be split for readability, but every phrase carries domain 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?

With an output schema present, the description does not need to explain return values, yet it usefully pre-frames the key response fields (karmicTail, loveLine, moneyLine, crossing). The one real gap is the absence of when-to-use guidance against the numerology siblings, which the rest of the package does not cover either.

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 67% and both `fields` and `precision` already carry their own schema descriptions, so the structured data does most of the work. The description only implies the birth-date input and adds no syntax or format detail for any parameter, so baseline 3 is right.

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 resource (the Destiny Matrix per Natalia Ladini, computed from a birth date) and enumerates the concrete outputs (personal square points A-E, ancestral corners, sky/earth lines, karmic/love/money chains). An agent can distinguish this from the numerology siblings by name and method. It stops short of an explicit contrast with the numerology family, so it is not 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 statement of when to pick this tool over the many numerology chart siblings, nor prerequisites beyond the implicit required `date`. The Group/Endpoint/Cost tags in context signals supply administrative framing, but the description itself offers no routing 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds genuinely useful operational context — cost (100 credits, Tier 4), the required-parameter set, and the endpoint. It stays silent on runtime behavior an agent might care about, such as whether the multi-round debate is long-running, streamed, or bounded in output size. The POST endpoint is not a contradiction of readOnlyHint, but it is worth noting.

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?

Tight and well front-loaded: the core operation comes first, then compact bracketed metadata. Every line carries information (endpoint, required fields, cost) rather than filler. Its brevity is a virtue, though it edges into under-specification.

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?

An output schema exists, so return values need not be described. But for an 8-parameter tool with a nested chart object, aless-than-40% coverage, and a cost of 100 credits, the description leaves critical gaps — most importantly the semantics of agentA/agentB and the effect of rounds/language.

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 38%, so the description carries a heavier burden, and it does not meet it. It restates the three required parameters that the schema already marks as required, but never explains what agentA/agentB actually are (persona strings? model IDs?) or what topic expects. Optional params like rounds, language, and fields get no mention.

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?

Uses a specific verb-and-resource phrasing: '2 personas debate a topic, multi-round transcript.' An agent can grasp the operation immediately. However it does not differentiate itself from close siblings such as astroway_mcp_multi_agent_coordinate, astroway_mcp_ai_chat, or astroway_mcp_ai_comparison_coach, which 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 when-to-use guidance and no named alternative. The bracketed metadata lists required fields and cost but never says when this debate tool is preferable to multi-agent coordination or AI chat. The [Group: MCP Advanced] tag is organizational, not decision-supporting.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint false, and openWorldHint false. The description adds useful behavioral context in the form of the cost (10 credits, Tier 1) and HTTP method (GET), but does not describe what the status output contains or any auth/rate-limit details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is short but poorly structured: a vague fragment followed by bracketed metadata lines. It is under-specified rather than concise, and the opening line does not front-load a clear purpose.

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?

Although an output schema exists and annotations cover the safety profile, the description still leaves the agent without a clear statement of what the tool does or when to call it. For a status endpoint in a large sibling set, this is a significant 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?

Schema description coverage is 100%, so the two optional parameters (fields, precision) are fully documented in the schema itself. The description adds no parameter meaning beyond the schema, so the baseline 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 gives only a fragment, '8 personas with specialties,' which hints at pool composition but never states that this tool returns agent pool status or what that status contains. It lacks a clear verb and resource, and does not distinguish itself from siblings like astroway_mcp_multi_agent_coordinate or astroway_agent_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 guidance on when to use this tool, when not to use it, or which sibling tool is the alternative. The description contains only metadata tags, not usage instructions.

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

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

Annotations already declare read-only, non-destructive, open-world behavior, so the bar is lower; the description still adds real behavioral facts beyond them — a 10-turn history ceiling, 21 output languages, four selectable voices via persona, and a concrete pricing rule (5 credits with your own provider key vs. the endpoint price). It stops short of stating auth requirements or what happens when the history limit is exceeded. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences: the differentiator first, capabilities second, pricing last, followed by a compact metadata block (group, endpoint, required param, tier cost). Every clause carries new information and nothing is repeated from the schema.

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 an output schema present the description needn't explain return values, and annotations cover the safety profile, so what remains — what the tool is for, its capability envelope, and its cost model — is covered. The main gap is that nothing tells an agent when this endpoint should be picked over the other AI/agent siblings.

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?

Top-level schema description coverage is only 43% (chart, fields and precision documented; message, persona, language and history not), so the description must compensate and partially does — it explains persona (four voices), history (~10 turns) and language (21 options). It says nothing about chart, fields compact-mode paths, or precision, though the nested chart schema does carry unusually rich self-documentation for those.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource — an AI chat answered from computed natal-chart positions rather than the model's prior knowledge of a sun sign — and quantifies scope (10 turns, 21 languages, 4 personas). It clearly implies a different product from sibling AI utilities such as astroway_mcp_ai_explain_aspect or astroway_mcp_ai_comparison_coach, but never names them, so the differentiation is by tone rather than explicit contrast.

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 rather than stated: the credit-price note ('send your own provider key and the turn costs 5 credits instead of the endpoint price') hints this is a paid, higher-tier call, and 'chart-grounded' hints the input needs birth data. There is no explicit when-to-use-it, when-not-to, or routing rule against the other chat/agent endpoints in 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true and idempotentHint=false, so the safety profile is covered. The description adds genuinely useful operational context (the 100-credit Tier 4 cost and the POST endpoint), but says nothing about the fact that an LLM-backed coach may return non-deterministic prose, what latency to expect, or what deprecates the idempotentHint=false signal.

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 four lines are tight and the purpose sentence is front-loaded ahead of the bracketed metadata block. Nothing is padded, though the metadata lines are boilerplate rather than definitional content.

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?

An output schema exists, so return values need not be explained, and the cost/endpoint block is present. But for a six-parameter AI tool embedded among dozens of similar compatibility siblings, the description lacks any hint of what the coaching output contains or what makes a good 'question', leaving the agent to guess at scope.

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 67% and the nested chart objects carry extensive inline documentation (formats, rejected short names, timezone semantics, houseSystem letters), so the schema does the heavy lifting. The description only restates the required parameters (chart1, chart2, question), adding no meaning for question, language, fields or precision. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (coach), the resources (two charts) and the domain (relationship dynamics), so the agent knows this produces interpretive guidance rather than raw chart data. It does not, however, distinguish itself from the many sibling compatibility tools (ashtakoot, dashakoota, compatibility_full) or from astroway_mcp_ai_chat, so sibling differentiation is left to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance, and no alternative is named. A reader cannot tell whether to reach for this AI coach versus the deterministic Vedic compatibility endpoints or multi_chart_context. The only constraints given are required parameters and cost, which are not usage 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true and idempotentHint=false, so the safety profile is covered without the description. The description does add genuinely useful operational context not present in the annotations: the credit cost (100 credits, Tier 4) and the endpoint. However it never explains why a read-only operation is flagged non-idempotent (repeated calls likely yield differently worded narrative), which is the one behavioral trait an agent would most want here.

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 purpose sentence is front-loaded and the payload is small. The '[Required: planet1, planet2, aspectType]' line duplicates the schema's required array, but the cost and endpoint lines justify their space.

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?

An output schema exists, so return values need not be described. But for a 7-parameter tool with a nested chart object and LLM-backed generation, the description omits the valid domain for planet1/planet2, any usage guidance versus explain_transit, and any hint about generation latency or variable output.

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 lists the three required parameters, but schema coverage is only 43% and planet1/planet2 carry no description, no enum and no example anywhere in the schema, so the agent must guess the accepted form (planet names such as 'Mars'?). The description does not compensate for that gap, which is the weakest part of the definition.

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?

Names a specific verb and resource: 'explanation of an aspect between two planets.' An agent can tell it apart from the sibling astroway_mcp_ai_explain_transit by the resource alone, but the description never makes that contrast explicit nor states what kind of explanation is produced.

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 when-to-use guidance, no prerequisites, and no mention of the sibling explain_transit as an alternative. The only contextual cues are bracketed metadata (endpoint, required fields, credit cost), which tell the agent what it costs but not 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?

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description usefully adds the cost (100 credits, Tier 4) and the endpoint, which annotations do not provide. It does not explain why idempotentHint is false for a read-only call, nor what the AI explanation entails.

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-loads the purpose before the bracketed metadata. The bracketed group/endpoint/required/cost lines are slightly noisy but each carries compact information, so there is little waste.

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?

An output schema exists, so return values need not be described. But for a 5-required-parameter tool with a near-twin sibling, the description omits the disambiguation, parameter usage, and cost implications an agent needs before committing. It is minimally adequate rather than 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 38%, so the description should compensate, but it merely restates the five required parameter names that the schema already marks required and says nothing about what transitPlanet, natalPlanet, aspectType accept or how the optional fields/precision/language parameters behave. It adds no meaning 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?

States a specific verb and resource: 'Explain a current transit hitting your natal chart.' An agent can grasp the purpose immediately. However, it never distinguishes itself from the close sibling astroway_mcp_ai_explain_aspect, leaving the borderline case 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?

There is no when-to-use guidance, no exclusions, and no comparison to the near-identical sibling astroway_mcp_ai_explain_aspect. The '[Required: ...]' and '[Cost: ...]' lines are metadata, not routing guidance. The agent gets no help deciding between this and other AI 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered structurally. The description usefully adds the cost (100 credits, Tier 4) and the endpoint/group, but says nothing about latency, response shape of the synthesis, or how many personas are permitted (schema caps at 4).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the operative sentence, followed by compact bracketed metadata; there is no filler prose. The brevity is close to under-specification rather than pure conciseness, keeping it out of the top band.

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?

An output schema exists so return values need not be described, and cost is disclosed. However, for a tool whose whole contract is choosing personas and a question, the description never explains what the agents array should contain, leaving the most decision-relevant input undocumented across both description and schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50% and the description adds no meaning beyond listing the two required names. Critically, the 'agents' array is the defining parameter and neither the schema nor the description explains what identifiers it accepts, and 'question' semantics are equally 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?

States a specific verb (Run), resource (N personas) and mechanism (parallel + LLM synthesis), which is more informative than a tautology. It does not name or distinguish itself from the obvious sibling astroway_mcp_agent_debate, so the agent must infer the difference between coordinated parallel personas and a debate.

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 when-to-use guidance, no prerequisites, and no alternatives are named despite several closely related siblings (agent_debate, multi_chart_context, ai_chat). The '[Required: question, agents]' line just restates the schema's required array rather than telling the agent when this tool is the right choice.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuinely useful non-annotation behavior: a 10-credit (Tier 1) cost and the POST endpoint. It says nothing about what the operation returns or how it behaves across the 1-6 chart array, so it earns only partial credit.

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 and front-loads the one-sentence purpose, with well-organized bracketed metadata. But that metadata is machine-oriented boilerplate (group/endpoint/required) and the prose line is largely redundant with the title, so the brevity reflects under-specification as much as discipline.

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?

An output schema exists, so return values need not be explained, but for a tool taking up to six nested chart objects with four intent modes and compact-mode fields/precision, the description is far too thin. It gives an agent no way to know what a "compatibility" vs "forecast" run produces or why to pick it over the many neighbouring multi-chart tools.

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 content is "[Required: charts]", which merely repeats the schema's required array, adding zero meaning. The description says nothing about `fields`, `precision`, or the four `intent` modes — the latter has no schema description at all despite being the main selector. At 50% schema coverage this is a real gap it fails to fill.

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?

"Compact context for MCP agents working across multiple charts" largely restates the name/title (multi-chart context) without naming an action or an output. The word "context" is undefined — it never says whether this computes cross-chart aspects, comparison summaries, or group forecasts. Only the bare notion "multiple charts" distinguishes it from the many single-chart 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 no when-to-use guidance at all: no trigger conditions, no prerequisites, and no routing against the large sibling set (e.g. astroway_mcp_multi_agent_coordinate or astroway_mcp_ai_comparison_coach). The `intent` enum (compatibility/family/group/forecast) suggests several distinct use cases, but the description never explains when to choose which.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered structurally. The description adds genuinely useful context the annotations do not: the endpoint, the 10-credit Tier 1 cost, and the group. It does not disclose result ordering, chunk granularity, or hit limits, so it stops short of rich 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?

Four short, front-loaded lines with no prose padding; the core purpose statement leads. The "Required" line is redundant with the schema, which is the only real waste.

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 taking a deeply nested chart object plus three tuning parameters, the description is thin: no sense of ranking/scoring semantics, no indication of what the chunks are drawn from, and no guidance on choosing topK. An output schema exists so return format need not be explained, but the retrieval behavior itself is left entirely to inference.

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 a middling 60%. The description adds no parameter meaning at all — it only echoes the two required names already enforced by the schema — and says nothing about topK's default/range, the fields compact projection, or precision, the parameter most likely to be misused.

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?

Names the mechanism (keyword-tag scoring) and the corpus (chart chunks), which goes beyond simply restating the tool name. However, it never says what the tool returns or what a "chunk" is, so an agent cannot tell whether this is a document retriever over interpretive text or a query over computed chart data.

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 usage-adjacent line is "[Required: query, chart]", which merely restates the schema's required list. There is no statement of when to reach for this tool rather than a direct retrieval sibling (e.g. astroway_mcp_multi_chart_context), and no prerequisites 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, so the safety profile is covered. The description adds genuinely non-derivable behavior: the response is delivered as an SSE stream rather than one payload, crediting at 100 credits (Tier 4), and the concrete endpoint. It omits auth requirements and why idempotentHint=false, which keeps it out of 5 territory.

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?

Short and front-loaded: the core capability leads, with bracketed metadata (group, endpoint, required param, cost) following compactly. Every line carries information, though the template-style [Group:]/[Endpoint:] format is more machine header than prose.

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 streaming tool with no output schema and a nested chart parameter, the definition covers the essential facts (SSE transport, required message, optional chart, cost). It does not describe what the stream emits or how chart context influences the completion, leaving gaps an agent would notice mid-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 60%, with the nested chart object heavily documented in the schema itself (timezone, houseSystem letters, lat/lon full names, ayanamsa). The description adds only 'optional chart context', which restates the schema's required list. Baseline 3 is appropriate when the schema does most of the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource+mechanism: 'Server-Sent Events streaming chat completion with optional chart context.' An agent can tell this is a streaming chat tool rather than a static computation. It does not explicitly name or contrast with the closest sibling astroway_mcp_ai_chat, 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?

No when-to-use or when-not-to-use guidance. Nothing tells the agent to prefer this over astroway_mcp_ai_chat (non-streaming chat) or astroway_mcp_tool_call_stream; the streaming qualifier implies a context but the choice is left entirely 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?

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds two genuinely useful behavioral facts annotations cannot express: delivery is server-sent events rather than a single response, and the call costs 10 credits (Tier 1). It still omits stream termination, error-over-stream behavior, and whether partial results can be replayed.

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?

Very short and front-loaded: one sentence of purpose followed by structured metadata brackets. Nothing is wasted, though the single sentence is so compressed that the core mechanics of the tool are never actually spelled out.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter tool with a nested free-form args object, a free-text tool selector, compact-mode options, and no output schema, this is under-specified. An agent cannot tell what the stream emits, how to consume it, or what valid values for tool are (presumably must match astroway_mcp_tools_list entries), all of which are load-bearing here.

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 40% across 5 parameters, and the description adds nothing beyond confirming that tool is required. args (arbitrary nested object forwarded to the target tool), language, and the compact-mode interplay of fields/precision are left entirely to the schema; the description should explain that args are passed through verbatim to the named 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?

"SSE-stream of a tool call envelope" names a delivery mechanism and an artifact, so the agent knows this is a streaming wrapper that executes a named tool. However, "tool call envelope" is opaque jargon and the definition never states the key fact that this proxies/executes another MCP tool by name, nor how it differs from the sibling astroway_mcp_streaming or astroway_mcp_tools_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?

The only usage cue is the bracketed "[Required: tool]" — there is no when-to-use, no when-not-to-use, and no routing to an alternative despite multiple plausible siblings (astroway_mcp_streaming, astroway_mcp_tools_list, astroway_agent_tools). The agent must guess whether streaming is preferred over a plain call.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context the annotations do not: the concrete GET endpoint and a cost caveat that this scope is not in the public credit manifest. It does not explain response size or pagination for a manifest that presumably enumerates all tools.

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 purpose sentence is front-loaded and the metadata tags are compact, but the bracketed group/endpoint/cost lines are boilerplate scaffolding rather than description content. Nothing is wasted, yet very little informational payload is delivered.

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?

An output schema exists so return-value documentation is not required, but for a meta-tool that enumerates the entire tool surface, the description never explains the scenario in which an agent would reach for it instead of directly invoking a domain tool. Given the enormous sibling set, this leaves a real 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 100%, so both `fields` and `precision` are already documented in the schema with examples and constraints. The description contributes no additional parameter meaning; the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

"Auto-generated tool manifest for MCP clients" largely restates the name 'MCP Tools List' without a distinct verb or an explanation of what the response actually contains. It gives an endpoint and spec version but no functional description that would distinguish its purpose from any other listing endpoint.

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 an agent should call this tool, what problem it solves, or how it relates to the ~190 sibling tools. The only contextual cues are the bracketed [Group]/[Endpoint]/[Cost] metadata tags, which are not usage 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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, covering the safety profile. The description adds genuinely useful meta-context the annotations do not: the credit cost (10 credits, Tier 1) and the POST endpoint. It says nothing about what the Balance number represents or how the result is shaped, but the output schema exists to cover that.

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 purpose sentence followed by compact bracketed metadata (group, endpoint, required fields, cost). Purpose is front-loaded, nothing is redundant, and the structured tags are scannable.

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 calculation tool with an output schema and full annotation coverage, the description supplies what the agent needs to invoke it: purpose, required inputs, endpoint and cost. The remaining gap is usage guidance against the many sibling numerology tools, which is scored separately.

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 50% (only fields and precision are documented in the schema; name and date are bare). The description implies name is a full name and restates the two required parameters, but adds no format or syntax detail beyond what the schema already encodes (e.g. the date pattern). Baseline 3 is appropriate given the partial coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate the Balance number') and disambiguates the system ('Numerology: Chaldean system'), which separates it from the Pythagorean, Kabbalistic and Vedic balance siblings. It also specifies the computation basis ('from initials of each part of the full name'), but it never names an alternative sibling to route against, so differentiation rests on the group tag rather than prose.

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 states required parameters and cost but gives no when-to-use context and no exclusions or alternatives. Nothing tells an agent why it would pick Chaldean balance over, say, astroway_numerology_kabbalistic_balance or astroway_numks_balance, nor when a Balance reading is 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?

Annotations already declare readOnly=true, idempotent=true, destructive=false, closed-world, so the safety profile is covered. The description adds a genuinely useful behavioral trait not in the annotations: the cost (10 credits, Tier 1) and the endpoint. It does not describe what the computation returns or how it behaves, but with annotations carrying safety and an output schema present, this is a solid addition.

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 core purpose is front-loaded in the first sentence, and the bracketed metadata (group, endpoint, required, cost) is compact and skimmable. No sentence is wasted, though the metadata block is fairly boilerplate rather than high-value prose.

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 an output schema present, return values need no explanation, and the annotations cover the safety profile. The description adds required params, cost, and endpoint, which is close to complete for a single-value calculation tool. The notable gap is the absence of any cross-system disambiguation, which is what keeps it from 5.

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 50%: 'fields' and 'precision' are documented in-schema, while 'name' and 'date' have no descriptions. The description lists the two required params and hints that 'date' supplies the day-of-birth digit, adding modest meaning, but it does not explain format, constraints, or the compact-mode params. A 3 is appropriate given the schema does part of the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Calculate the Birthday number') and pins the system via 'Numerology: Chaldean' plus the group tag, which separates it from the many sibling *_birthday tools (kabbalistic, pythagorean, vedic, numks). 'From the day-of-birth digit' clarifies the input semantics beyond the bare name. It stops short of contrasting the output with other systems' birthday numbers, so 4 rather than 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 Chaldean birthday tool over pythagorean_birthday, kabbalistic_birthday, or vedic_birthday, nor any prerequisite or exclusion. The metadata block lists required params and cost but never frames selection context. An agent must infer the choice purely from the tool name.

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

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds a genuinely non-structured behavioral fact, the cost ('10 credits (Tier 1)'), which matters for agent budgeting decisions, plus the HTTP endpoint. It does not cover latency, auth, or response shape (output schema exists).

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 front-loaded sentence with the core purpose, followed by compact bracketed metadata lines and no filler. Slightly cluttered by the redundant '[Required: ...]' line, which costs a little but nothing is verbose.

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 specialized calculation tool with an output schema, the description supplies purpose, inputs, cost, and endpoint, which is enough to call it correctly. It omits only usage guidance relative to sibling systems, and return values are covered by the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50%; 'fields' and 'precision' are documented in the schema, while 'date' and 'name' carry only patterns/length constraints. The description merely restates '[Required: name, date]', which the schema already declares, and adds no meaning for the compact-mode parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate four Challenge cycles') and qualifies the domain ('life-area difficulties to master, derived from birth date components'). The 'Chaldean system' tag distinguishes it from the Pythagorean/Vedic/Kabbalistic challenge siblings, though the differentiation relies on that tag rather than an explicit contrast.

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 statement of when to use this tool versus the ~70 sibling numerology tools, no prerequisites, and no exclusions. The '[Group: ...]' and '[Endpoint: ...]' lines are routing metadata, not usage 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?

Annotations already establish read-only, idempotent, non-destructive behavior, so the description's added value is the cost disclosure (20 credits, Tier 2) and the localization contract: every number carries `meaning` plus `meaningLocalized`, with `translated: false` returning English while a language's strings are being prepared. That fallback behavior is the kind of thing an agent could not infer from structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core value proposition (six numbers in one call) and then layers cost and localization in tight sentences. Slightly dense with parenthetical caveats, but every clause carries information an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter computation tool with annotations and an output schema, this is nearly complete: it covers the member set, cost, localization, and the year default. The only gap is silence on the `fields`/`precision` compact-mode controls, which are relevant given the tool returns a large nested payload.

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 60%, so `year`, `fields` and `precision` are documented in the schema while `name` and `date` are not. The description clarifies that `year` defaults to the current year and confirms `name`/`date` are required, but says nothing about the `fields`/`precision` compact-mode parameters, leaving the schema to carry them. Baseline 3 fits when the schema does most of the lifting.

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 verb+resource: returns the six core numbers (Life Path, Expression, Soul Urge, Personality, Birthday, Personal Year) in one call, under the Chaldean system. The enumeration lets an agent distinguish it immediately from the single-number siblings like astroway_numerology_chaldean_life_path. It also names the sibling it supersedes ('six single 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?

It makes the selection case clear by contrasting cost: '20 credits instead of 60 for six single calls', which routes an agent wanting a full chart here rather than making six separate calls. It stops short of an explicit 'use X when / don't use Y when' statement or naming the individual sibling tools, so it is strong context rather than 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds the cost (10 credits, Tier 1) and the POST endpoint, which is genuinely useful behavioral context, but says nothing further about response behavior or limits.

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 definition is short and front-loads the core purpose in the first sentence, with the bracketed metadata kept compact. Every element earns its place, though the tag block adds some structural noise.

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?

An output schema exists so return values need not be explained, and the tool is a simple idempotent read. However, the role of the required 'date' parameter and the lack of any guidance distinguishing this system's Expression number from the many sibling Expression tools leave it only minimally 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 50%: 'fields' and 'precision' are documented in the schema, while 'name' and 'date' are not. The description clarifies 'name' as the full birth name, but never explains what 'date' represents (birth date vs. reference date) or its format, leaving a meaningful semantic gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (calculate Expression/Destiny number) and specifies both the letter basis (all letters, reduced) and the Chaldean system, which separates it from the vowel-based soul_urge or the pythagorean/kabbalistic/vedic expression siblings. It does not explicitly name an alternative, but the systematic sibling naming plus the 'all letters' and 'Chaldean' qualifiers make its identity inferable.

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 when-to-use or when-not-to-use guidance and no routing to alternatives such as astroway_numerology_pythagorean_expression or the kabbalistic/vedic variants. The [Group: Numerology: Chaldean] tag implies the domain but gives no selection criteria, leaving usage entirely 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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and a closed-world scope, so the safety profile is covered. The description usefully adds the cost ('10 credits, Tier 1') and the POST endpoint, which is real behavioral context beyond the annotations, but says nothing about what the calculation returns or any input constraints.

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?

Compact and front-loaded: the core action leads, followed by bracketed metadata lines. No wasted prose, though the bracket-tag format is more machine-oriented than descriptive.

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?

An output schema exists, so return values needn't be explained, and annotations cover safety. However, for a tool with a documented output and two undocumented input params, the description omits usage routing and any note on the name/date semantics, leaving an agent to infer a fair amount.

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 50%: 'fields' and 'precision' are well documented in the schema, but 'name' and 'date' carry no schema descriptions. The description adds 'year + month + day, reduced' for the date and restates the two required params, giving marginal clarification over the pattern already in 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?

States a specific verb (Calculate) and resource (Life Path number) with the input basis (birth date, year+month+day reduced) and names the numerological system (Chaldean). This distinguishes it from the Pythagorean, Kabbalistic, and Vedic life-path siblings, though it does not differentiate from other Chaldean tools. Clear and specific, but largely echoes the title.

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 when-to-use guidance or alternatives are offered. The bracket tags give required params, endpoint, and cost, but never explain when Chaldean life-path is preferred over the many other life-path tools. The agent must infer usage from the 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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavioral context beyond annotations: a credit cost ('10 credits (Tier 1)') and the concrete endpoint, which help an agent budget and route the call.

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 substantive sentence is front-loaded, single-purpose and wastes no words. The trailing bracketed metadata block is boilerplate rather than prose, but it is compact and skimmable rather than rambling.

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?

An output schema exists, so return values need not be explained, and the description covers purpose, formula, required inputs, cost and endpoint. The remaining gap is input interpretation (whose name, birth vs current) and no note on how the result should be interpreted age-wise.

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 50% (fields and precision are documented in-schema; name and date are not). The description only repeats 'Required: name, date', adding no meaning over the schema's required array and no clarification of what form the name should take. It does not compensate for the undocumented parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate the Maturity number'), identifies the system (Chaldean), and even gives the underlying formula (sum of Life Path and Expression), which distinguishes it from the many sibling *maturity* tools for other systems. It stops short of explicitly contrasting against e.g. pythagorean_maturity or life_path, relying on the system label alone.

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 when-to-use or when-not-to-use guidance: nothing says when to pick Chaldean over Pythagorean/Kabbalistic maturity, or when maturity is preferred to its component numbers (life_path, expression). The 'activates around age 35' note is interpretive context for the number, not invocation 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?

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description usefully adds cost (10 credits, Tier 1) and the endpoint, but says nothing about auth requirements, rate limits, or what the calculated output contains beyond what the output schema provides.

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 core explanation is a single front-loaded sentence, with grouped metadata in compact brackets. Every element earns its place, though the bracket block is slightly noisy relative to the short prose.

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-value compute tool with an output schema, the description covers what is calculated and from what input, so return values need no explanation. It is nonetheless thin on routing among the ~70 numerology siblings, which is the main contextual 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 coverage is 50%: `fields` and `precision` are documented in the schema, but `date` is not, and the description does not explain the date's role. It does add real semantic value for `name` by specifying it must be the full birth name whose consonants drive the calculation — meaning not present in 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 names a specific verb and resource — 'Calculate the Personality number' — and narrows it to the Chaldean system and to the consonants of the full birth name. That is enough to separate it from the many pythagorean/kabbalistic/vedic personality siblings, though it never explicitly contrasts 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 statement of when to choose this over astroway_numerology_kabbalistic_personality or pythagorean_personality, or when a Personality number is the right reading versus Soul Urge/Expression. The only guidance is the bracketed 'Required: name, date', which is input plumbing rather than 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, covering the safety profile. The description adds genuinely useful operational context (10 credits / Tier 1, POST endpoint, required inputs), but says nothing about response shape or the default-year behavior that materially affects results.

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 one-line purpose sentence is front-loaded and waste-free, and the bracketed metadata block is scannable. Slightly verbose for the amount of substance but structurally sound.

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?

An output schema exists, so return values need not be explained, and the description supplies endpoint, cost, required inputs and system variant. The only gap is the absence of cross-system routing guidance, which matters given ~10 indistinguishable personal_year siblings.

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 60% (year, fields, precision documented; name and date only constrained by pattern/length). The description's '[Required: name, date]' merely restates the schema's required array and adds no format or range detail for those two parameters, so it neither compensates for nor improves on 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?

States a specific verb ('Calculate'), resource ('Personal Year number'), input scope ('for a given calendar year') and the semantic meaning ('9-year cycle of personal evolution'). The explicit 'Chaldean system' tag disambiguates it from the many sibling personal_year tools in kabbalistic/pythagorean/vedic/numk/numks/nump variants.

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 on when to choose this tool over the near-identical personal_year siblings from other numerological systems, nor any prerequisites beyond the [Required: name, date] block. The tool name and group tag carry all the routing burden.

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

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description contributes the credit cost (10 credits, Tier 1) and required-input list, which are genuinely useful operational details, but says nothing about output shape or failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One tight prose line followed by scannable bracketed metadata (group, endpoint, required, cost). Front-loaded and free of filler, though the metadata partially duplicates structured fields.

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?

An output schema exists, so return values need not be described. Combined with annotations covering the safety profile and the description supplying cost, endpoint and required inputs, an agent has enough to invoke it correctly; only the conceptual distinction from sibling readings is 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 bracketed '[Required: name, date]' restates what the schema already enforces, and the two optional compact-mode params (fields, precision) carry their own schema descriptions. At 50% schema coverage the description neither compensates for the undescribed name/date semantics nor adds format hints beyond the schema pattern.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate four Pinnacle cycles with their age boundaries') plus the system (Chaldean), which distinguishes it from the Kabbalistic, Pythagorean and Vedic pinnacles siblings. It stops short of contrasting the concept against other Chaldean tools such as chart or challenge.

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 on when to choose Pinnacle cycles over the many other Chaldean numerological readings (chart, challenge, maturity, personal_year). The only routing signal is the group/endpoint metadata, which tells the agent what family the tool belongs to but not the condition that selects 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?

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely useful behavioral context not in annotations: the POST endpoint, the required inputs, and a 10-credit Tier 1 cost. It does not disclose return shape, though an output schema exists.

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 core purpose is front-loaded in a single clear sentence, followed by compact bracketed metadata. Nothing is redundant, though the bracketed block reads as boilerplate rather than prose that earns each line.

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?

An output schema exists, so return values need not be described, and the description covers purpose, required inputs, and cost. What is missing is the routing context that matters most here — why an agent should pick this over the ~10 other soul-urge variants across systems.

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 50%; `fields` and `precision` are documented in the schema, while `name` and `date` have no schema descriptions. The description partially compensates by specifying that `name` should be the full birth name, but explains nothing about the format of `date` or why a date is needed for a name-derived vowel calculation. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate the Soul Urge number') plus the derivation method ('from the vowels of the full birth name') and the system ('Chaldean'). This distinguishes it from the personality counterpart (consonants) and from Pythagorean/Vedic/Kabbalistic variants, though it never names those siblings explicitly.

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 when-to-use guidance or routing advice against the many sibling numerology systems (kabbalistic, pythagorean, vedic soul_urge tools all exist). The bracketed lines only list group, endpoint, required params, and cost — metadata rather than usage context.

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

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered structurally. The description adds genuinely useful operational context the annotations do not carry: the POST endpoint, the 10-credit Tier 1 cost, and the required input pair. It stops short of describing the response, but that is covered by the output 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?

One front-loaded functional sentence followed by compact bracketed metadata blocks for group, endpoint, required inputs and cost. Nothing is padded, though the metadata bracket repeats 'kabbalistic' already implied by the title.

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?

An output schema exists, so return values need not be described, and cost/endpoint/required inputs are present. However, the unexplained meaning of `date` and the silence on the non-strict vs strict kabbalistic distinction leave real gaps for a tool with four parameters and many near-identical siblings.

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 50%: the `fields` and `precision` compact-mode parameters are already documented in the schema, while `name` and `date` carry no descriptions. The description adds only that `name` is the full name whose initials are used; it never explains what role `date` plays in a 'balance' calculation. Baseline 3 is appropriate given the schema does part of the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Calculate the Balance number from initials of each part of the full name,' and pins the system as Kabbalistic (phonetic). It is clearly distinguishable from the Chaldean/Pythagorean/Vedic balance siblings, but it never addresses serial variants like astroway_numerology_kabbalistic_strict_balance, so the sibling differentiation is incomplete.

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 when-to-use guidance, no statement of when to prefer this over the strict or other-system balance tools, and no preconditions beyond the required-parameter list. The agent is left to infer selection purely from the tool name.

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

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond annotations: the credit cost (10 credits, Tier 1), the endpoint, and the required inputs. It does not disclose output format or any failure/validation behavior, but the output schema exists to cover returns.

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 operative sentence is front-loaded and zero-waste; the bracketed metadata lines are compact and scannable. Slightly redundant to repeat 'Required: name, date' which the schema already enforces.

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 annotations covering safety and an output schema covering returns, the description is nearly sufficient – cost and endpoint are helpful additions. Its main shortfall is the absence of any signal distinguishing it from the 'strict' kabbalistic variant, which is the one decision an agent actually has to make here.

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 50% – the required 'name' and 'date' have no schema descriptions, while 'fields' and 'precision' do. The description compensates only partially by stating that the day-of-birth digit drives the calculation and listing required params, but adds no format or range detail beyond the regex already in the schema. Baseline 3 fits.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate the Birthday number') and pins the variant with 'Kabbalistic (phonetic) system' and 'from the day-of-birth digit', which separates it from Chaldean/Pythagorean/Vedic birthday tools and from the kabbalistic_strict sibling. It does not, however, explain what makes it distinct from astroway_numerology_kabbalistic_strict_birthday beyond the 'phonetic' qualifier.

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 when-to-use, when-not-to-use, or alternative guidance is given. The bracketed metadata ('Required: name, date', cost) is administrative, not usage selection help, and nothing steers an agent between this and the many sibling birthday variants.

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

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

Annotations already establish the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds genuinely useful operational context beyond them: the endpoint (POST /v1/numerology/kabbalistic/challenge) and a billing cost of 10 credits at Tier 1, which affects whether an agent should spend the call. It does not describe failure modes or validation behavior, keeping it short of a 5.

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 operative sentence leads, followed by compact bracketed metadata for group, endpoint, requirements, and cost with no filler prose. The one weakness is that the metadata block repeats the schema's required list, a minor redundancy rather than bloat.

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 an output schema present, return values need not be explained, and the description covers purpose, system, endpoint, cost, and required inputs. For a four-parameter tool where the two optional compact-mode parameters are schema-documented, this is largely sufficient; only the ambiguity with the 'strict' sibling and the bare name/date semantics leave 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 50%: `fields` and `precision` are documented in the schema, while `name` and `date` have no descriptions and the description only restates that they are required. It adds nothing about name handling (phonetic system implies spelling sensitivity) or the date format beyond the schema's pattern, so it neither compensates for nor worsens the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate four Challenge cycles') plus a concrete definition of what Challenge cycles are ('life-area difficulties to master, derived from birth date components'). It also names the numerological system ('Kabbalistic (phonetic)'), which routes away from Chaldean/Pythagorean/Vedic siblings, but it gives no basis to distinguish this from the near-identical astroway_numerology_kabbalistic_strict_challenge 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?

Naming the Kabbalistic (phonetic) system implies when this variant applies versus Pythagorean or Vedic, and the required-parameters line signals the input precondition. However, there is no explicit when-to-use/when-not guidance and no mention of the 'strict' variant that shares the same system, so selection still requires inference from the tool name.

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

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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description still adds real operational context: the 20-credit cost, and the localization caveat that `meaningLocalized` may fall back to English with `translated: false` while a language's strings are pending.

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 return contents and the cost comparison are front-loaded, and the bracketed group/endpoint/required/cost block is scannable. It is slightly dense with metatext, but no sentence is wasteful for a tool with this many sibling variants.

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?

An output schema exists, so return values need not be explained, yet the description still previews `meaning`/`meaningLocalized`. Required inputs are surfaced via the bracket line. The only gap is that the referenced language selection has no corresponding parameter, leaving the localization trigger ambiguous.

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 60%, with `year`, `fields` and `precision` already documented in the schema, so baseline is 3. The description restates the `year` default (already in the schema) and mentions meanings come 'in the requested language', but no language parameter exists in the schema, so that hint is unactionable rather than additive.

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?

Names a specific verb+resource (returns the six core numbers in one call) and enumerates them: Life Path, Expression, Soul Urge, Personality, Birthday, Personal Year. It also states the system variant ('Kabbalistic (phonetic)') and the concrete alternative ('60 for six single calls'), which separates it from both the single-number siblings and the other chart schools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly frames the use case: get all six numbers together for 20 credits rather than issuing six single calls, which is a clear cost/coverage trade-off an agent can act on. It does not, however, tell the agent when to prefer a sibling such as astroway_numerology_kabbalistic_strict_chart or the Chaldean/Pythagorean/Vedic chart variants.

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

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful non-annotation context — endpoint, required inputs, and a 10-credit Tier 1 cost — but says nothing about name normalization, failure behavior, or why a date is needed for a name-derived number.

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 tight sentence with the operation front-loaded, followed by a compact metadata block. The bracketed lines are boilerplate but each carries a distinct fact (group, endpoint, required params, cost), so little is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-shape explanation is correctly omitted, and annotations cover the safety profile. The remaining gaps are the unexplained role of 'date' and the absence of routing guidance against the strict and other-system expression siblings, which matters in a family this dense.

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 50%: 'fields' and 'precision' are self-documented, while 'date' and 'name' are not. The description partially compensates by stating both are required and clarifying that the full birth name is used with all letters counted, but it never explains what 'date' represents (birth date?) for a calculation driven by name letters.

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 specific verb and resource ('Calculate the Expression (Destiny) number') and pins the system as 'Kabbalistic (phonetic)'. That differentiates it from the Chaldean, Pythagorean and Vedic expression siblings, though it never addresses the near-identical astroway_numerology_kabbalistic_strict_expression, which is the sibling an agent is most likely to confuse it with.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: the '(phonetic)' label and '(all letters, reduced)' method identify the variant, so an agent can infer this is the phonetic-Kabbalistic variant rather than the strict one. There is no explicit when-to-use statement, no exclusion of the strict/Chaldean/Pythagorean alternatives, and no prerequisite 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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds one genuinely useful behavioral fact, the billing cost (10 credits, Tier 1), plus the required-parameter list, but says nothing about determinism, rate limits, or how name participates in a birth-date calculation.

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 core purpose is front-loaded in the first sentence, with the second sentence giving the system qualifier. The bracketed metadata lines are terse and skimmable, though the endpoint line duplicates information an MCP client does not need to make a selection.

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?

An output schema exists, so return values need no explanation, and the operation itself is simple. Still, for a tool sitting in a cluster of five near-duplicate life-path variants, the description omits the guidance that would let an agent pick this one confidently, and it leaves the role of `name` unexplained.

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 only 50%: `fields` and `precision` are documented in-schema, while the two required params (`date`, `name`) have no schema descriptions. The description's "birth date (year + month + day, reduced)" partially compensates for `date`, but it never explains why a `name` is required for a life-path calculation, leaving a real ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Calculate the Life Path number") and names the system variant ("Kabbalistic (phonetic)"), which separates it from the Chaldean/Pythagorean/Vedic life-path siblings. However, it does not differentiate from the near-identical siblings astroway_numerology_kabbalistic_strict_life_path and astroway_numks_life_path, so an agent still has to guess among those.

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 when-to-use or when-not-to-use guidance and no mention of the alternative life-path tools in the enormous sibling set. The only routing signal is the system label baked into the name and description, leaving the strict vs phonetic distinction 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?

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is fully covered. The description adds the endpoint and a concrete cost of 10 credits (Tier 1), which is genuinely useful agent-relevant context, but says nothing about rate limits or response behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first sentence and the metadata block is compact and scannable. Every element earns its place, though the bracketed metadata could be slightly tighter.

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 an output schema present, return values need no explanation, and annotations cover safety. Cost, endpoint, required params, and system are all stated, leaving only cross-system selection guidance as an 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?

Schema description coverage is 50%, and the description only repeats 'Required: name, date', which the schema's required array already conveys. It adds no format or meaning for either parameter and does not compensate for the two documented compact-mode params it ignores.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Calculate), the exact resource (Maturity number), its derivation (sum of Life Path and Expression), its meaning (activates around age 35), and the system (Kabbalistic/phonetic). The system label lets an agent distinguish it from the Pythagorean, Vedic, Chaldean, and 'strict' Kabbalistic variants among the many 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 no when-to-use/when-not guidance and no alternatives named, even though siblings like kabbalistic_strict_maturity and the other systems are direct substitutes. 'Activates around age 35' describes the number itself, not when an agent should call this 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?

Annotations already declare readOnly/idempotent/destructive=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: the credit cost (10 credits, Tier 1) and the concrete endpoint, which an agent can use for budgeting. It stops short of describing the response, but that is less critical here.

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 core purpose is front-loaded in a single clear sentence, with metadata (group, endpoint, required, cost) cleanly bracketed afterward. Slightly label-heavy, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the annotations carry the safety profile. The description covers purpose, system, endpoint, required inputs, and cost. The main gap is the absence of any guidance on choosing between the many near-identical sibling personalities.

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%; 'fields' and 'precision' are documented in-schema but 'name' and 'date' are not. The description partly compensates by clarifying that 'name' is the full birth name and that only consonants are used, plus listing the required inputs, but it adds nothing about the compact-mode parameters. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Calculate'), resource ('the Personality number'), input derivation ('from the consonants of the full birth name'), and system ('Kabbalistic (phonetic)'). This is enough to distinguish it from the many sibling personality tools (chaldean, pythagorean, vedic, kabbalistic_strict) without opening their schemas.

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 identifies the system and the required inputs but offers no explicit when-to-use, when-not, or alternative routing (e.g., vs. kabbalistic_strict_personality or pythagorean_personality). Usage is only implied by the group label and name.

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

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely useful metadata beyond annotations: cost (10 credits, Tier 1), endpoint, and required inputs. It still says nothing about what the calculation returns or what 'personal evolution' output looks like, and an output schema exists to carry that, so this is adequate rather than rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose in the first clause, followed by a compact bracketed metadata block (group, endpoint, required, cost). No filler sentences. Slightly dense but every element carries routing or cost 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?

For a simple computation tool with an output schema and full safety annotations, the essentials (purpose, required inputs, cost) are present. The omission is disambiguation from the many parallel Personal Year implementations, which matters far more here than return-value detail that the output schema already supplies.

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 60%: `year`, `fields`, and `precision` are documented in-schema, while `date` and `name` carry only pattern/length constraints. The description merely repeats the required list ('Required: name, date') and adds the phrase 'for a given calendar year', adding no meaning beyond structured fields. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate the Personal Year number') and pins the system ('Kabbalistic (phonetic)'), which is essential given ~70 sibling numerology tools. It does not, however, distinguish itself from near-identical siblings such as kabbalistic_strict_personal_year or numk_personal_year, so an agent cannot tell those apart from the text alone.

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 when-to-use guidance and no mention of alternatives. It never tells the agent how this differs from the chaldean, pythagorean, vedic, strict, numk, numks, or nump Personal Year variants, which is the single most important routing decision for this tool family. The system label is implied context, not 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?

No contradiction with annotations, which already declare readOnly/idempotent/non-destructive/closed-world. The description adds genuinely useful operational context the annotations do not carry: the endpoint path, required inputs, and a 10-credit Tier 1 cost. It says nothing about computation inputs beyond name/date or any output traits, but the output schema covers returns.

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?

Punchy and front-loaded: the functional sentence leads, and bracketed metadata follows in a scannable block. Every line carries information, though the '[Group:]' line partially duplicates the school already stated in the first sentence.

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 an output schema present and safety annotations covering the risk profile, the main completeness gap is the absence of any routing guidance in a family of ~10 near-duplicate pinnacle tools. Operational facts (endpoint, cost, required fields) are present, so the definition is adequate but leaves the agent to guess which sibling applies.

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 50%: 'fields' and 'precision' are documented in the schema itself, while 'name' and 'date' have only length/pattern constraints. The description merely restates the two required params ('Required: name, date') and adds no format or behavior detail beyond the schema, which is the expected baseline 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?

States a specific verb and resource ('Calculate four Pinnacle cycles with their age boundaries') and identifies the school as 'Kabbalistic (phonetic) system', which separates it from the chaldean/pythagorean/vedic pinnacles siblings. It does not, however, explicitly distinguish itself from the near-identical 'kabbalistic_strict_pinnacles' variant, so a qualifier about the phonetic vs strict distinction is missing.

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 lists required parameters and cost but never says when to choose this tool over the many sibling pinnacle calculators. There are no usage conditions, prerequisites, or named alternatives despite an extremely crowded sibling namespace.

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

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

Annotations already declare readOnly/idempotent/non-destructive/non-open-world, so safety is covered; the description adds genuinely new behavioral context: the cost (10 credits, Tier 1), the endpoint and method, and the required inputs. It does not describe the shape or limits of the computation, but the cost/credit disclosure is meaningful budget-relevant information beyond the structured fields.

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 front-loaded sentences carry the substance, and the bracketed metadata lines are compact and scannable. Slightly over-tagged (five metadata blocks for a four-parameter calculation tool), but there is no wasted prose.

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?

An output schema exists, so return values need not be described, and annotations carry the safety profile. What remains is adequate for a simple deterministic calculation: system variant, required inputs, and cost are all present. The one loose end is the unexplained `date` parameter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (only `fields` and `precision` are documented), and the description only adds '[Required: name, date]'. It does partially compensate by implying `name` is the full birth name (vowels taken from it), but it never explains what role `date` plays in a vowel-based soul-urge calculation, leaving a real ambiguity unresolved.

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?

Names a specific verb and resource (calculate the Soul Urge number) and the input basis (the vowels of the full birth name), and pins the variant with 'Kabbalistic (phonetic) system'. That variant tag is exactly what separates it from the many sibling soul_urge tools (chaldean, pythagorean, vedic, strict) without opening their schemas.

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 [Group] and [Endpoint] tags plus the 'Kabbalistic (phonetic)' label let an agent infer this is the kabbalistic-family soul-urge calculation, but nothing states when to prefer it over chaldean/pythagorean/vedic or over the near-identical 'strict' and 'numks' siblings. No alternatives or exclusions are named, so guidance is implied rather than explicit.

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

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

Annotations already declare this as a read-only, idempotent, non-destructive, closed-world operation, so the safety profile is covered. The description adds genuinely decision-relevant context not present in structured fields: the endpoint, the required inputs, and a billing cost of 10 credits (Tier 1), which an agent should weigh before calling.

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 core sentence is front-loaded and carries no filler, and the bracketed metadata lines are structured rather than prose padding. The metadata block is slightly redundant with the schema's required list, but the format is scannable and cheap.

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?

An output schema exists, so return values need not be described, and cost/endpoint/required inputs are supplied. What is missing is the differentiation and selection logic an agent needs when eleven near-identical Balance siblings are available, particularly the strict/non-strict boundary.

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%: `fields` and `precision` are documented in the schema, while `date` and `name` carry no schema description. The prose clarifies that `name` supplies initials of each part of the full name, but the role of `date` in a name-derived Balance calculation is never explained anywhere.

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 computation (Balance number) plus the exact input basis (initials of each part of the full name) and names the numerology system (Kabbalistic, Mathers strict). It distinguishes itself from the Chaldean/Pythagorean/Vedic Balance siblings, but never clarifies how 'kabbalistic_strict' differs from the plain 'astroway_numerology_kabbalistic_balance' sibling, which is the closest and most confusable alternative.

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 choose this tool, no prerequisites, and no routing to or away from alternatives. The 'strict' vs non-strict distinction is left entirely to inference despite both tools existing side by side.

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

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful non-annotation context — cost ('10 credits (Tier 1)') and the required-parameter list — but says nothing about authentication, rate limits, or what the computation consumes (e.g., whether 'name' actually influences the result).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action in the first sentence, and the bracketed metadata lines are compact and scannable rather than prose padding. Slightly fragmented structure, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described, and the annotations carry the safety profile. However, for a tool sitting in a dense family of near-identical siblings, the description omits the strict-vs-non-strict distinction and the role of the 'name' parameter, which are the two things an agent most needs.

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 50%: 'fields' and 'precision' are documented in the schema while 'date' and 'name' are not. The description adds one hint — that the number derives from the 'day-of-birth digit' — but does not explain why 'name' is required for a day-digit calculation, leaving a real semantic gap. Baseline 3 is appropriate at this coverage level.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Calculate') and resource ('Birthday number from the day-of-birth digit') and names the divination system ('Kabbalistic (Mathers strict) system'), which is the key discriminator among the many numerology siblings. It falls short of a 5 because it never explicitly distinguishes itself from astroway_numerology_kabbalistic_birthday (non-strict) or astroway_numks_birthday, which an agent must otherwise infer.

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 system label ('Kabbalistic (Mathers strict)') and the endpoint path give implied selection context among the Chaldean/Pythagorean/Vedic/Kabbalistic variants. There is no explicit when-to-use statement, no condition that selects the strict variant over the plain Kabbalistic one, and no exclusion 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral context in the credit cost (10 credits, Tier 1), but says nothing about response shape, error cases, or rate limits beyond that.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core verb+resource+system in the first sentence, followed by short bracketed metadata lines that scan quickly. No filler prose; the only redundancy is restating the required parameters already implied by the schema.

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?

An output schema exists, so return values need not be explained, and the cost plus required inputs are disclosed. For a parameterized calculation endpoint with four params this is nearly complete, with only minor gaps around what the `name` input contributes to a challenge calculation.

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% — `fields` and `precision` are documented in the schema, while `date` and `name` carry only type/pattern constraints. The description merely restates the required set ('Required: name, date') and hints at birth-date derivation; it adds no format, meaning, or interaction detail beyond the schema for the undocumented half.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Calculate four Challenge cycles: life-area difficulties to master') and pins the system variant ('Kabbalistic (Mathers strict) system'), which is exactly what separates it from the plain astroway_numerology_kabbalistic_challenge sibling. An agent can pick this tool over the non-strict and Chaldean/Pythagorean/Vedic challenge variants without opening any schema.

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 choose this Challenge tool over the sibling challenge/chart variants, nor any prerequisites or exclusions beyond which parameters are required. The [Group]/[Endpoint]/[Cost] tags are metadata, not usage guidance, so routing must be inferred entirely from the name.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds real beyond-annotation context: the credit cost tipping, the localized-meaning fields, and the translated:false fallback behavior during localization. It stops short of describing any rate limits or failure modes.

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 core value proposition is front-loaded, cost follows, then output shape, then system. It is dense but every clause contributes; only the bracketed metadata footer is boilerplate.

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 an output schema present, return structure needn't be explained, and the description still covers cost, localization semantics, the system variant, and the aggregation advantage. Nothing an agent needs to invoke it correctly 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?

Schema coverage is 60% and the schema itself documents year (defaults to current year), fields, and precision, so the description repeats the year default rather than adding syntax. It references 'the requested language' as if a language parameter exists, but no such property is in the schema, adding slight ambiguity rather than clarity.

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?

It names the exact resource (the six core numbers: Life Path, Expression, Soul Urge, Personality, Birthday, Personal Year) and the system (Kabbalistic Mathers strict), which distinguishes it from the plain kabbalistic_chart and the single-number siblings. An agent can tell what it returns and which tradition it belongs to without opening the schema.

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 cost framing ('20 credits instead of 60 for six single calls') gives a clear reason to choose this aggregate tool over the six per-number siblings. However, no explicit when-not condition or named alternative is stated, so routing is inferred rather than prescribed.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context the annotations do not: the cost (10 credits, Tier 1) and the endpoint, which matter for agent budget and routing decisions. It stops short of describing the return payload, but the output schema exists.

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 core purpose is front-loaded in a single efficient sentence, followed by bracketed metadata that is scannable and non-redundant. The tag block is slightly administrative but each entry (group, endpoint, required, cost) carries distinct 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?

With an output schema present and annotations covering the safety profile, the description's remaining burden is method and invocation context, both of which are supplied (strict Kabbalistic method, required params, cost). The one soft spot is that the role of 'date' is never stated, though it is conventional for numerology.

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 50%: fields and precision are documented in the schema, but date and name are not. The description compensates for the name parameter by clarifying it must be the full birth name with all letters reduced, which is the semantically ambiguous one. It adds nothing for date, so the coverage gap is only partly closed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Calculate), a specific resource (Expression/Destiny number), and the exact computation rule (full birth name letters, all letters, reduced). It also names the system variant 'Kabbalistic (Mathers strict)', which lets an agent distinguish it from the many sibling expression tools (kabbalistic_expression, pythagorean_expression, vedic_expression, etc.) without opening their schemas.

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 named system variant implies which sibling family this belongs to, so routing is partially inferable. However, there is no explicit when-to-use statement, no guidance on choosing strict vs non-strict Kabbalistic, and no mention of prerequisites or exclusions beyond the '[Required: name, date]' tag.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds genuinely useful operational detail beyond annotations: the credit cost (10, Tier 1), the endpoint, and required inputs, which help an agent budget and call correctly.

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?

Purpose is front-loaded in the first sentence, with structured bracketed metadata following. Nothing is wasted, though the bracket lines are slightly boilerplate-heavy relative to the terse core sentence.

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?

An output schema and rich annotations are present, so return values and safety need not be described. The main gap is differentiation from the extremely crowded sibling set (kabbalistic vs kabbalistic-strict vs other systems), which the description only partially addresses via the system label.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.