Learn organizational terminology from a GitHub Pull Request. Extracts planning terms from PR title/description and maps them to changed code files. Use dryRun to preview before persisting.
Accepts raw HTML/template content (prData.body); Accepts URL/endpoint input (prData.url); Accepts file system path (prData.changedFiles[].filename); High parameter count (16 properties)
Part of the Lingo MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents call learn_from_pr to retrieve information from Lingo without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though learn_from_pr only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
tools:
learn_from_pr:
rules:
- action: allowSee the full Lingo policy for all 13 tools.
Agents calling read-class tools like learn_from_pr have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.
Learn organizational terminology from a GitHub Pull Request. Extracts planning terms from PR title/description and maps them to changed code files. Use dryRun to preview before persisting.. It is categorised as a Read tool in the Lingo MCP Server, which means it retrieves data without modifying state.
Add a rule in your Intercept YAML policy under the tools section for learn_from_pr. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Lingo MCP server.
learn_from_pr 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 learn_from_pr rule in your Intercept 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 Intercept policy for learn_from_pr. 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.
learn_from_pr is provided by the Lingo MCP server (@hyukyyy/lingo-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.