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Get CLI Feedback

get_cli_feedback

Retrieve CLI feedback items from Codecks project management, with optional filtering by category to identify bugs, improvements, or missing features.

Instructions

Read saved CLI feedback items. Optionally filter by category. No auth needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNo

Implementation Reference

  • The get_cli_feedback tool handler implementation - reads saved CLI feedback from .cli_feedback.json file, optionally filters by category, and returns the results using finalizeToolResult
    async (args) => {
      try {
        if (!existsSync(FEEDBACK_PATH)) {
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify(finalizeToolResult({ found: false, items: [], count: 0 })),
              },
            ],
          };
        }
        const data = JSON.parse(readFileSync(FEEDBACK_PATH, "utf-8"));
        let items: Record<string, unknown>[] = data?.items ?? [];
        if (args.category) {
          items = items.filter((i) => i.category === args.category);
        }
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(
                finalizeToolResult({
                  found: items.length > 0,
                  items,
                  count: items.length,
                }),
              ),
            },
          ],
        };
      } catch (err) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(finalizeToolResult(handleError(err))),
            },
          ],
        };
      }
    },
  • Tool registration for get_cli_feedback with title, description, and input schema (optional category filter)
    server.registerTool(
      "get_cli_feedback",
      {
        title: "Get CLI Feedback",
        description: "Read saved CLI feedback items. Optionally filter by category. No auth needed.",
        inputSchema: z.object({
          category: z
            .enum(["missing_feature", "bug", "error", "improvement", "usability"])
            .optional(),
        }),
  • Helper constants and error handling function used by the feedback tools
    const FEEDBACK_PATH = resolve(process.cwd(), ".cli_feedback.json");
    const MAX_ITEMS = 200;
    
    function handleError(err: unknown): Record<string, unknown> {
      if (err instanceof CliError) return contractError(String(err), "error");
      return contractError(`Unexpected error: ${err}`, "error");
    }
Behavior3/5

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 mentions 'No auth needed,' which is a useful behavioral trait, and implies a read-only operation ('Read'), but it doesn't cover other aspects like rate limits, pagination, or response format. This leaves gaps in transparency for a tool with zero annotation coverage.

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 extremely concise with just two sentences that directly convey key information: the action, resource, optional filtering, and an auth note. Every sentence earns its place without any wasted words, making it front-loaded and efficient.

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?

Given the tool's low complexity (1 optional parameter) and no output schema, the description is somewhat complete but lacks details on return values or behavioral constraints. With no annotations, it should ideally cover more aspects like response format or error handling to be fully adequate.

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?

The input schema has 1 parameter with 0% description coverage, but the description adds value by explaining that 'category' is used for optional filtering. However, it doesn't detail the enum values or provide further semantic context beyond what the schema's enum implies, so it partially compensates but not fully.

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 ('Read') and resource ('saved CLI feedback items'), making the purpose evident. However, it doesn't explicitly differentiate this tool from potential siblings like 'list_activity' or 'list_conversations', which might also involve reading data, so it doesn't reach the highest score.

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 provides some usage context by mentioning optional filtering by category, but it lacks explicit guidance on when to use this tool versus alternatives (e.g., compared to other 'list_' tools). It also doesn't specify prerequisites or exclusions, leaving usage somewhat implied.

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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