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shenchensucc

Chen's AI Copy

by shenchensucc

add_interested_company

Add companies to track for job applications or collaboration opportunities, including roles, sectors, and notes for career planning.

Instructions

Add a company Chen is interested in applying to or working with.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCompany name
sectorNoOptional: industry sector
notesNoOptional: notes
rolesOfInterestNoOptional: roles of interest

Implementation Reference

  • The actual implementation of addInterestedCompany, which loads the interested companies from a JSON file, checks for duplicates, and saves the updated list.
    export async function addInterestedCompany(company: InterestedCompany): Promise<void> {
      const companies = await loadJson<InterestedCompany[]>("interested_companies.json", []);
      if (!companies.some((c) => c.name.toLowerCase() === company.name.toLowerCase())) {
        companies.push(company);
        await saveJson("interested_companies.json", companies);
      }
    }
  • Type definition for InterestedCompany which defines the structure of the input required for the tool.
    export interface InterestedCompany {
      name: string;
      sector?: string;
      notes?: string;
      rolesOfInterest?: string[];
      lastChecked?: string;
    }
  • src/index.ts:75-92 (registration)
    The MCP tool definition and registration for add_interested_company in the server's listTools response.
      name: "add_interested_company",
      description:
        "Add a company Chen is interested in applying to or working with.",
      inputSchema: {
        type: "object",
        properties: {
          name: { type: "string", description: "Company name" },
          sector: { type: "string", description: "Optional: industry sector" },
          notes: { type: "string", description: "Optional: notes" },
          rolesOfInterest: {
            type: "array",
            items: { type: "string" },
            description: "Optional: roles of interest",
          },
        },
        required: ["name"],
      },
    },
  • The MCP tool request handler block in src/index.ts that parses arguments and calls the addInterestedCompany function.
    if (name === "add_interested_company") {
      const companyName = safeArgs.name as string;
      if (!companyName) {
        return {
          content: [{ type: "text", text: "Error: name is required" }],
          isError: true,
        };
      }
      await addInterestedCompany({
        name: companyName,
        sector: safeArgs.sector as string | undefined,
        notes: safeArgs.notes as string | undefined,
        rolesOfInterest: safeArgs.rolesOfInterest as string[] | undefined,
      });
      return {
        content: [
          {
            type: "text",
            text: `Added interested company: ${companyName}`,
          },
        ],
      };
    }
Behavior2/5

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

No annotations are provided, yet the description fails to disclose critical behavioral aspects such as whether this creates a persistent record, how it handles duplicates, or what permissions are required. It only states high-level intent without explaining side effects, idempotency, or success conditions that an agent needs to invoke the tool properly.

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 a single, efficiently constructed sentence that front-loads the verb and contains zero redundant words. It delivers the core purpose immediately without unnecessary filler or tautology.

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

Completeness3/5

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

While the description adequately covers the tool's purpose and leverages complete schema documentation, it lacks behavioral details expected for a mutation tool given the absence of annotations and output schema. It omits information about return values, error states, or the persistence model that would help an agent understand the full operation context.

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

Parameters3/5

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

With 100% schema description coverage, the parameter names and types are self-documenting; the description adds minimal semantic value beyond implying the domain context for 'rolesOfInterest'. It meets the baseline expectation but does not elucidate parameter relationships, validation constraints, or format requirements beyond what the schema already provides.

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

Purpose4/5

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

The description clearly states the action ('Add') and object ('a company'), with specific scope indicating this is for Chen's job search interests. It effectively distinguishes this from sibling tools like `add_learning` through the distinct resource type and domain context, though it could specify what system the company is being added to.

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

Usage Guidelines3/5

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

The description implies usage context ('interested in applying to or working with') suggesting job search tracking scenarios. However, it lacks explicit guidance on when to prefer this over `get_context` or `update_preference`, and does not address prerequisites such as whether the company already exists.

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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