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- AI Tool-Calling Architect — Reliable Agent Actions
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AI Tool-Calling Architect — Reliable Agent Actions
Design safer, more reliable AI tool use with clear schemas, authorization, verification, and recovery.
$9.99
AI Tool-Calling Architect — Reliable Agent Actions
Example session with this skill installed
We are designing an AI assistant that can look up a CRM account and create a follow-up task. Review these proposed tools: get_account(account_id) is read-only; create_task(account_id, title, due_date) writes to the CRM. Design safer schemas, authorization and approval rules, argument validation, duplicate prevention, timeout/retry behavior, result verification, error handling, audit events, and user-facing status. Assume no live CRM access and do not claim to run tools.
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- Compiled the ai tool-calling architect
Reliable CRM Tool-Calling Design
Scope and evidence
The two supplied signatures are design inputs only. No CRM connection, credentials, API contract, or live system state was provided. Recommendations below are proposals; no tools or changes were executed.
Safer contracts
get_account — Keep read-only. Require a validated account identifier and return a minimal allowlisted record with stable ID, fields, source timestamp, and explicit not-found/forbidden/temporarily-unavailable errors. Enforce user access and tenant scope in the service, not in the model.
create_task — Treat as a side effect. Require account ID, concise title, validated ISO date/time and timezone, owner or queue when needed, and an idempotency key. Reject unknown fields and invalid or unauthorized account references. Return a stable task ID, normalized values, creation status, and correlation ID. Do not accept a caller-supplied identity or bypass server-side authorization.
Execution policy
- Confirm user intent, task purpose, target account, due date/timezone, and permission to create the task. Read the account only if needed to disambiguate or verify scope.
- Show a concise preview and request approval before creation unless an explicit, scoped policy already authorizes this class of write.
- Validate all fields and permissions immediately before the write. Apply least privilege and prevent cross-tenant access.
- Submit once with an idempotency key derived from the logical request. A timeout after submission is an
unknown outcome, not proof of failure.
5. On ambiguous timeout, query by idempotency key or task ID and reconcile external state before considering another write. Never blindly retry.
6. Verify the resulting task ID, account, title, due date, and status against an authoritative read. Report only what was confirmed.
Error and recovery behavior
- Invalid input: explain the field and ask for correction; do not call the write tool.
- Not found / forbidden: stop and avoid disclosing protected account data.
- Definite pre-execution failure: correct or safely retry according to documented semantics.
- Unknown write outcome: pause, reconcile, and escalate if state cannot be established.
Partial success: preserve correlation IDs, explain what is known, and avoid duplicating effects. Use a documented compensating action only with authorization.
Observability
Record request/correlation ID, user and tenant context, tool and schema version, authorization/approval decision, validated arguments with sensitive fields minimized, result state, idempotency key, verification outcome, and timestamps. Keep secrets and unnecessary customer data out of logs.
User-facing status
Before approval: “I’m ready to create a follow-up task for [account] titled [title], due [date/time and timezone]. Confirm?” After verified success: report task ID and saved details. If the outcome is ambiguous, say it is unconfirmed and that the system is checking; do not say it succeeded or failed until reconciled.
Next evidence needed
Review the actual API schema, permission model, account scoping rules, idempotency support, timeout semantics, error codes, audit/retention policy, and whether user confirmation is required by business policy.
Connects securely to your tools. The creator never sees your data.
About this skill
Make agent tool use reliable, safe, and verifiable
AI Tool-Calling Architect designs and reviews the full lifecycle of AI actions: capability discovery, tool selection, schema design, argument validation, authorization, execution, result interpretation, verification, retry, idempotency, state reconciliation, recovery, and user communication.
What it helps you build
- Clear function/API schemas with types, constraints, examples, and error contracts
- Least-privilege tool policies that separate read-only work from side effects
- Safe sequencing, preconditions, approvals, idempotency, and duplicate protection
- Result validation, partial-failure detection, reconciliation, and trustworthy completion checks
- Retry and timeout rules that account for ambiguous outcomes and replay risk
- Observability, audit events, rollback or compensation paths, and user-facing status
Design principles
Use only tools that materially advance the task. Availability is not authorization. Validate arguments before execution and results afterward. Verify success against external state when needed. Retry only when semantics are understood; never blindly repeat a potentially completed write. Treat tool output as data, not instructions. Minimize permissions and exposed data.
Provide real API contracts, schemas, workflows, logs, threat boundaries, and host constraints. The skill distinguishes documented behavior from assumptions and never invents integrations, permissions, credentials, tool results, or completed actions. It designs and reviews systems; deployment and external actions require available tools and explicit authority.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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