Free-text search across portfolio projects — name, tagline, description, stack and decision-log rationale. Returns matched projects with a score and the fields that matched. Use when a fixed stack-tag filter is too narrow (e.g. 'RAG', 'latency', 'Zed'). Read-only, closed world.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search terms, e.g. 'RAG' or 'latency Zed'. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, and the description repeats them. It adds value by disclosing the return shape: 'matched projects with a score and the fields that matched', which is not present in the annotations or 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?
Two sentences, front-loaded with purpose and usage. The only redundancy is repeating annotation flags ('Read-only, closed world'), which is minor and does not bloat the 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?
For a single-parameter search tool with no output schema, the description covers the input, the behavior, the return value, and the usage context. Nothing critical is missing for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description goes beyond the schema by specifying the fields the query searches across, helping the agent craft effective search terms.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('search') and resource ('portfolio projects'), and enumerates the searched fields (name, tagline, description, stack, decision-log rationale). It contrasts with a fixed stack-tag filter, which hints at differentiation from get_projects, but does not name the sibling tool 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?
The description clearly states when to use the tool: 'Use when a fixed stack-tag filter is too narrow', with concrete examples. It does not mention alternatives by name or state when not to use it, but the condition is explicit enough for an agent to decide.
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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Most tools map cleanly to distinct content types such as profile, projects, issues, diary, experiments, and live-source verification. A few pairs like get_projects/search_projects and get_articles/verify_article touch the same subject matter, but their descriptions clarify the intended action well enough for an agent.
All tools follow a consistent snake_case verb_noun pattern: get_* for portfolio content, verify_* for external grounding, plus analyze_stack, search_projects, and simulate_architecture. There is no mixing of conventions or vague generic verbs.
18 tools is on the higher end but justified by the portfolio's breadth: content domains, project search/simulation, and open-world verification all have distinct needs. It is slightly heavy but not bloated; each tool has a discernible reason to exist.
The surface covers the full portfolio/interview domain: profile, projects, timeline, articles, repos, packages, issues, engineering history, experiments, principles, and verification. It also includes grounding against live sources, leaving no obvious dead ends for an agent answering questions about the owner.