A
license-
qualityC
maintenanceEnables semantic search over an Obsidian vault using natural language, retrieving relevant notes and extracted conclusions.
MIT
xkcd Comic Suggester
Server Details
Suggests a relevant xkcd comic during a conversation, via semantic search over every comic.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- papjuli/xkcdai
- GitHub Stars
- 0
- Server Listing
- xkcdai
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Tool Definition Quality
A4.7/5.0
Tool DescriptionsA
Average 4.9/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
Only one tool exists, so there is no possibility of ambiguity or overlap between tools.
Naming Consistency5/5
With a single tool, naming is inherently consistent and follows a clear verb_noun pattern (find_xkcd).
Tool Count3/5
The server has only one tool, which feels thin and borderline for its purpose. While it could be sufficient for a focused suggestion function, it limits the server's utility.
Completeness4/5
The single tool effectively covers the core purpose of semantically suggesting xkcd comics. However, it lacks auxiliary operations like fetching a specific comic by number or retrieving random comics, which are minor gaps.
Available Tools
1 toolfind_xkcdAInspect
Find xkcd comics semantically relevant to the current conversation.
Call this whenever an xkcd comic might enrich the conversation — when the
discussion lands on a topic xkcd is famous for skewering (programming, science,
statistics, relationships, the absurdity of standards, etc.).
Pass a concise description of the current topic or theme as `context` (a phrase
or sentence works better than a whole transcript), e.g. "spending hours
automating a task that was faster to do by hand" or "code finally compiling".
IMPORTANT — deciding whether to mention one. xkcd has a comic for almost every
topic, so this tool will nearly always return something. A result being
returned does NOT mean you should bring it up. Use the `score` as a signal and
apply your own judgment about conversational fit:
score >= 0.75 strong match — usually worth mentioning if it fits the moment
0.66 - 0.75 plausible — mention only if it genuinely lands
< 0.66 weak/tangential — almost always better to stay silent
Only one comic, at most, per topic — and only when it actually adds something.
When you do share one, cite it by number and title with its `url`, and quote
the `alt` (mouseover) text — it's half the joke.
Returns a dict with a `results` list (num, title, score, url, image, alt,
explain_url) and a `count`. An empty list means nothing cleared the floor.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| context | Yes | ||
| min_score | No | ||
| max_results | No |
Tool Definition Quality
A4.9/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the burden of behavioral disclosure. It explains that the tool returns a results list with scores, that an empty list means nothing cleared, and that the tool does not automatically decide to mention a comic—the agent must apply judgment. This is comprehensive and sets correct expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured: it starts with purpose, then usage guidelines, then parameter tips, then output format. Each sentence adds value. A slight reduction for minor redundancy (e.g., the IMPORTANT section could be tighter), but overall efficient.
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?
Given the tool has 3 parameters, no output schema, and no annotations, the description is remarkably complete. It covers when to use, how to phrase input, how to interpret results, and even how to cite results. An empty list return is documented. No gaps remain for agent confusion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description adds significant meaning: it explains the 'context' parameter with examples and how to phrase it, it indirectly explains 'min_score' by describing score thresholds, and 'max_results' is implied. The defaults are noted in schema but the description adds operational context.
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 finds xkcd comics semantically relevant to the conversation, with specific verb ('find') and resource ('xkcd comics'). Despite no sibling tools provided, the purpose is unambiguous and self-contained.
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?
Provides explicit guidance on when to call (topics xkcd is known for) and when not to mention a result even if returned. Includes a detailed score threshold breakdown (0.75+, 0.66-0.75, <0.66) to guide conversational judgment, which is rare and highly useful.
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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