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delete_test_suite

Delete a test suite on a Keploy branch — synchronous, no playbook to walk. USE THIS when: * The dev's update_test_suite call was rejected with "preserves no steps from the existing suite — that's a full rewrite, not an edit". Delete the existing suite and re-author from scratch via create_test_su...

Part of the Keploy server.

delete_test_suite can permanently delete data in Keploy, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents may call delete_test_suite to permanently remove or destroy resources in Keploy. Without a policy, an autonomous agent could delete critical data in a loop with no way to undo the damage. PolicyLayer blocks destructive tools by default and requires explicit human approval before enabling them.

Without a policy, an AI agent could call delete_test_suite in a loop, permanently destroying resources in Keploy. There is no undo for destructive operations. PolicyLayer blocks this tool by default and only allows it when a human explicitly approves the action.

Destructive tools permanently remove data. Block by default. Only enable with explicit approval workflows.

policy.json
{
  "version": "1",
  "default": "deny",
  "hide": [
    "delete_test_suite"
  ]
}

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These attack patterns abuse exactly the kind of access delete_test_suite gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so delete_test_suite only ever does what you allow.

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Other destructive tools across the catalogue. The same approach applies to each: deny by default, or require human approval.

What does the delete_test_suite tool do? +

Delete a test suite on a Keploy branch — synchronous, no playbook to walk. USE THIS when: * The dev's update_test_suite call was rejected with "preserves no steps from the existing suite — that's a full rewrite, not an edit". Delete the existing suite and re-author from scratch via create_test_suite. The error message itself routes here. * The dev explicitly says "delete the suite", "remove suite X", "wipe my orderflow suite". * A genuine wholesale redesign — every step changed in shape — that the audit trail shouldn't try to reconcile as edits. DO NOT USE THIS when: * The dev wants a real edit (one assertion, one step's body). Use update_test_suite + preserve existing step IDs instead — keeps audit history intact. * The dev wants to "redo" a single failed run. Test runs are independent of suite state; just rerun via replay_test_suite. INPUT * app_id (required) — Keploy app id * suite_id (required) — UUID of the suite to delete * branch_id (required) — Keploy branch UUID. The delete creates a branch-scoped DeleteTestSuite audit event so reads on the same branch see the suite as gone. Direct main writes are blocked. OUTPUT * On success: {"deleted": true} — suite is tombstoned at the branch overlay; subsequent reads (getTestSuite / listTestSuites) on this branch return 404 / exclude it. * 404 if the suite_id doesn't exist on this app/branch (verify via getTestSuite or listTestSuites first if you're unsure). After delete, the standard re-create flow is: (1) call create_test_suite with a freshly authored steps_json. The new suite gets a fresh suite_id; the old id is tombstoned, not reusable. ═══════════════════════════════════════════════════════════════════ DISCOVERY — when the dev hands you a bare suite_id with no app_id / branch_id: ═══════════════════════════════════════════════════════════════════ Suites live on a (app_id, branch_id) tuple. A bare suite_id has no on-disk hint about which app or branch holds it; you have to RESOLVE both before calling this tool. Walk these steps in order — STOP as soon as getTestSuite returns 200: 1. Detect the dev's git branch: Bash git rev-parse --abbrev-ref HEAD in app_dir. If exit non-zero / output is "HEAD" → not a git repo / detached HEAD; ASK the dev for the Keploy branch name (don't invent one). 2. Resolve candidate apps via the cwd basename: Bash basename $(pwd) → call listApps with q=<basename>. Usually 1–2 candidates. If 0 → ASK; if >1 → walk every candidate in step 4. 3. For each candidate app, call list_branches({app_id}) and find the branch whose name matches the git branch from step 1. That gives you {branch_id}. If no match → not this app, try next. 4. Verify with getTestSuite({app_id, suite_id, branch_id=<from step 3>}). 200 → resolved; 404 → wrong app/branch, try next. 5. If steps 2–4 exhaust, walk every OPEN branch on each candidate app, then try main (branch_id omitted). If still nothing → ASK the dev for the {app_id, branch_id} pair. After resolving once in a session, REUSE the {app_id, branch_id} for subsequent suite-targeted calls; don't re-walk discovery for every action.. It is categorised as a Destructive tool in the Keploy MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.

How do I enforce a policy on delete_test_suite? +

Register the Keploy MCP server in PolicyLayer and add a rule for delete_test_suite: 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 Keploy. Nothing to install.

What risk level is delete_test_suite? +

delete_test_suite is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.

Can I rate-limit delete_test_suite? +

Yes. Add a rate_limit block to the delete_test_suite 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.

How do I block delete_test_suite completely? +

Set action: deny in the PolicyLayer policy for delete_test_suite. 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.

What MCP server provides delete_test_suite? +

delete_test_suite is provided by the Keploy MCP server (https://api.keploy.io/client/v1/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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