search_within
Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search...
This record as markdown: /tools/io-github-pipeworx-io-linear/search-within.md
What search_within does on Linear
AI agents call search_within to retrieve information from Linear without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
text | string | Yes | The document text to search inside (max ~200K chars). |
limit | number | — | Max passages to return (1-20, default 5). |
query | string | Yes | Natural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin". |
Parameters from the server's own tool schema.
Why search_within is rated Low
The tool performs semantic search over already-fetched text and returns filtered passages with metadata (offsets, scores). It does not modify, delete, execute code, or move data. It is purely a Read operation that retrieves and queries information from a document the user has already obtained.
From the tool's definition Semantic search INSIDE a fetched record. Pass the text you already pulled... get back the top-N passages with character offsets and similarity scores... search_within saves context, returns only the passages that matter.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs search_within safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Linear, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For search_within, this is the rule to start with:
search_within is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Linear, apply this rule, and every search_within call is checked against it from then on.
Questions about search_within
Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged). It is categorised as a Read tool in the Linear MCP Server, which means it retrieves data without modifying state.
search_within accepts 3 parameters: text, limit, query. Required: text, query. The full parameter table on this page comes from the server's own tool schema.
Register the Linear MCP server in PolicyLayer and add a rule for search_within: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Linear. Nothing to install.
search_within is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the search_within rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for search_within. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
search_within is provided by the Linear MCP server (https://gateway.pipeworx.io/linear/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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