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by dev.weblens

project_due_diligence

Off-chain due diligence on a project's web presence — the half an on-chain rug checker cannot see. Returns domain age and registrar, whether a team page, whitepaper, docs and socials exist, whether the site is an off-the-shelf template, and a cross-check of a contract address against the addresses actually printed on the project's own website (a mismatch is a strong impersonation signal). Gives weighted risk signals and an A-F grade. Reads NOTHING on-chain — pair it with a contract/liquidity checker. Price: $0.05

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoOptional chain label, e.g. base, ethereum, solana
domainYesProject website, e.g. "example.org"
tokenAddressNoOptional contract address to cross-check against the site

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool reads nothing on-chain, discloses the cost ($0.05), and clarifies the scope as off-chain web presence analysis. It doesn't mention rate limits or response handling, but the key side-effect and cost information is present.

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

Conciseness5/5

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

The description is three sentences: it states the purpose, lists concrete outputs, and ends with a pairing recommendation and price. Every sentence contributes meaningful information, with no redundancy or fluff.

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

Completeness5/5

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

Since there is no output schema, the description appropriately details the return values (domain age, registrar, content presence, template detection, contract cross-check, risk grade). It also includes cost and pairing context, making it a self-contained description that fully prepares an agent to use the tool.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds extra meaning by explaining that the optional contract address is used for cross-checking against the project's website, which clarifies the purpose of tokenAddress beyond the schema text. The domain parameter's role is also implied through the output list.

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

Purpose5/5

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

The description clearly states the tool performs off-chain due diligence on a project's web presence and enumerates specific outputs (domain age, registrar, team page existence, template detection, contract cross-check). It explicitly distinguishes itself from on-chain rug checkers, making its purpose and scope unmistakable.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: it reads nothing on-chain and should be paired with a contract/liquidity checker. This tells the agent when to use it (off-chain web checks) and when not to rely on it (on-chain analysis), even though it doesn't name sibling tools.

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

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TDQS

B3.2/5.0
Disambiguation2/5

Several tool clusters have near-overlapping purposes: fetch_webpage/fetch_webpage_pro/fetch_resilient and batch_fetch/get_contents are hard to distinguish, and answer_question/research/deep_research differ mainly in price and depth. The search_* and intel_* families are clearer, but the core fetching and research overlap creates ambiguity.

Naming Consistency3/5

Most tools follow a verb_noun snake_case pattern (fetch_webpage, search_web, extract_data), but there are notable exceptions like domain_intel, package_intel, youtube_transcript, memory_set, and intel_company, where the prefix/suffix convention is inconsistent. Still, the naming is broadly readable.

Tool Count2/5

35 tools is a large surface, far beyond the typical 3-15 range. The server covers many research verticals, but the number feels bloated, especially with multiple fetch and research variants that could be consolidated.

Completeness4/5

The tool set covers a wide range of web research needs: searching, fetching, crawling, extracting, screenshots, domain/tech/package intelligence, and market/competitive analysis. It lacks obvious lifecycle operations for monitors (list/delete/update) and memory (get/delete), but core workflows are well covered.

Resources