Oddi Forge

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

No annotations are provided, so the description carries the full burden; it discloses the topic coverage an agent gets back, which is the main behavioral trait here. It does not say whether answers are static or current, nor anything about return shape, but for a zero-parameter read-only lookup the risk surface is minimal.

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

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

A single front-loaded sentence identifying the resource followed by a compact topic list; nothing is wasted and nothing is buried.

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

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

With no parameters, no annotations, and no output schema, the description's main job is to scope the content, and the enumerated topics do that adequately. The only gap is that the boundary with the facts/news siblings remains 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 tool takes no parameters, so there is nothing for the description to disambiguate; baseline 4 applies. Schema coverage is 100% with no inputs to document.

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

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

States a specific resource and content type ('answers to common questions about Oddi Forge') and enumerates the covered topics (launch, contract, tokenomics, rewards, safety). An agent knows what it will get, though it does not explicitly distinguish this from get_project_facts, which likely overlaps on tokenomics and contract.

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

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

Usage is implied by 'common questions', suggesting this is the first stop for general inquiries, but there is no explicit when-to-use or when-to-prefer-get_project_facts / get_latest_news wording. Uniqueness among five siblings is left to inference.

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

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

No annotations exist, so the description carries the full disclosure burden. It implies a read of recent content but never states ordering (newest-first?), freshness window, whether results can be empty, or that access is public/unauthenticated. 'Latest' is the only behavioral hint and is undefined.

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 compact sentence with no filler; the subject (latest blog posts) is front-loaded. Slightly redundant in restating the title, but nothing wasteful.

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 zero-required-param read tool this is close to adequate, but with no annotations and no output schema, the description could have clarified the shape of a returned post (title/date/url) or the default freshness. It is minimally sufficient 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 coverage is 100% — the single `limit` parameter already documents type, range 1-10, and the default of 5. The description adds no meaning beyond that, so the baseline of 3 for a fully-documented schema 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 the resource clearly: 'the latest posts from the blog', with 'Oddi Forge's official news and updates' scoping the source. An agent can distinguish it from siblings (get_faq, get_project_facts, get_team, how_to_join) without opening the schema, though the verb is implicit rather than stated.

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

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

No indication of when to choose this over the sibling tools — e.g., whether it's for time-sensitive announcements versus static facts from get_project_facts. No exclusions, prerequisites, or alternative routing are provided.

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

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

With no annotations, the description carries the full burden, but this is a zero-parameter read-only lookup with little risk to disclose. It does add one useful behavioral detail: the contract address is conditional ("if launched"), signalling that a missing or pre-launch value is a legitimate outcome rather than an error. It says nothing about freshness guarantees or what happens if no facts exist yet.

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

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

Two sentences: the first front-loads purpose with a compact content enumeration, the second is a single-sentence activation rule. Nothing is redundant with the title or restates the tool name without adding 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 no-parameter, no-output-schema retrieval tool, the description gives enough for an agent to decide to call it and to anticipate the covered domains. The main remaining ambiguity is scope relative to siblings (e.g. what belongs in get_faq or get_latest_news instead), which the description leaves implicit.

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

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

The tool takes no parameters, so the baseline is 4. The description appropriately spends no words on parameter semantics and instead describes the fixed content the call returns.

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

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

The description names the resource precisely ($ODDI facts for Oddi Forge) and enumerates the covered content: launch status, contract address, tokenomics, vesting, rewards, safety rules and links. That makes it clearly a canonical-facts lookup rather than news, FAQ, or team info, though it doesn't explicitly name which sibling to use for adjacent questions.

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?

"Use this before saying anything about $ODDI" is a direct, actionable usage rule that tells the agent when to reach for this tool. It does not state when NOT to use it or point at alternatives like get_faq or get_latest_news for non-fact content, which is the only gap.

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

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

No annotations exist, so the description carries the disclosure burden, but a zero-parameter getter with no side effects needs little. It reveals the kind of record returned (founder, labelled agents, roles) yet says nothing about response shape, whether the roster is static, or how labels are presented.

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

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

A single compact sentence that front-loads the subject ('Who builds Oddi Forge') and then enumerates the contents. No filler or redundancy.

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

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

With no output schema, the description does at least sketch what is returned — a pseudonymous founder, openly labelled AI agents, and their roles. For a trivial parameterless read that is nearly enough; only return format and scope of 'roles' remain unspecified.

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

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

The schema has zero properties and full coverage, so there is nothing for the description to disambiguate. Baseline for a parameterless tool 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 names a specific resource — the founder and AI agent team behind Oddi Forge, including their roles — so an agent knows exactly what content comes back. It does not explicitly contrast itself with siblings like get_project_facts or get_faq, but the team/people framing is distinct enough in practice.

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: an agent can infer this is the tool for 'who is on the team' questions. There is no explicit statement of when to prefer it over get_project_facts or get_faq, and no exclusions or prerequisites are given.

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

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

With no annotations, the description carries the full burden, and it discloses the most important trait: this is a passive information lookup and the actual signup/email confirmation happens on the user's side, not through the tool. It doesn't say whether the answer is static or time-sensitive (e.g. whether the waitlist is open), which is the remaining behavioral unknown.

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

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

Two short sentences: the first says what the answer contains, the second says what to do with it. No filler, and the content statement is front-loaded.

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

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

For a no-parameter, no-annotation informational tool with no output schema, this covers what is returned (join link plus benefits) and the agent's role in presenting it. A little more on the shape of the answer or whether the waitlist status can change would make it complete.

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

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

The tool takes zero parameters, so the baseline of 4 applies. The description correctly implies no input is needed and none of its text invents parameter concepts.

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 the content precisely: how a person joins the Oddi Forge waitlist and what they get. This is topically distinct from the sibling getters (faq, news, project facts, team). It lacks an explicit verb like 'Returns' or 'Get', so a reader has to infer it is an informational lookup rather than an action.

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?

'Share the link with the user' gives clear operational guidance on what to do with the result, and 'the user signs up and confirms their email themselves' draws a hard boundary on what the agent must not attempt. It does not name when to prefer a sibling (e.g. get_faq for related questions), so routing guidance is only implied by topic.

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