More screenshots

    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    AI Tool Call Chain Integrity & Cost Receipt

    1

    Verify local AI tool-call and output logs for missing pairs, schema drift, duplicate calls, error outcomes and supplied cost-limit breaches.

    $9

    Secure checkout via Stripe

    30-day refund guarantee

    Converts to your local currency at checkout

    0 installsSecurity scanned
    AI Tool Call Chain Integrity & Cost Receipt

    AI Tool Call Chain Integrity & Cost Receipt

    Example session with this skill installed

    Review my authorized local exports tool-calls.jsonl and tool-outputs.jsonl against tool-catalog.json and cost-limits.json. Create a new packet in ./tool_call_review, identify missing pairs, duplicate calls, schema drift, error outcomes and supplied cost-limit breaches.

    • Read your context and instructions
    • Compiled the ai tool call
    • Generated the data export

    Tool-call integrity review complete

    The two exported logs were joined locally by exact call ID. The source files were not modified, and evidence-receipt.json binds all inputs and generated outputs with SHA-256.

    CheckSample result
    Calls inspected86
    Exact call/output pairs82
    Missing outputs2
    Orphan outputs1
    Argument-schema findings3
    Duplicate fingerprint groups2
    Error outcomes4
    Supplied usage cost$18.42 of $20.00 limit

    Findings requiring review

    • call_041 and call_078 have no matching output record.
    • output_legacy_02 refers to a call ID absent from the supplied call log.
    • Three calls include undeclared argument fields under the supplied tool catalog.
    • Two repeated-call groups share normalized tool name and arguments; they are reported as candidates and were not automatically treated as billing duplicates.
    • Four matched outputs declare an error status.

    Files created

    call-matrix.csv provides one row per joined record, duplicate-call-groups.csv groups repeated fingerprints, cost-summary.csv totals the supplied costs, issues.jsonl stores findings, and TOOL_CALL_INTEGRITY.md provides the human review. result.json and evidence-receipt.json preserve totals and hashes.

    Next steps

    Investigate the missing pairs and repeated groups using the original run context. Confirm costs against the vendor invoice if billing accuracy matters. The checker did not execute tools, recount tokens, grade output meaning or prove that any logged action occurred.

    ai-tool-call-chain-integrity-cost-receip.csv

    CSV · data export

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Detect orphaned tool calls missing their corresponding outputs.Identify schema mismatches between tool definitions and actual logs.Audit agent execution history for cost-limit policy violations.Generate deterministic integrity receipts for compliance and debugging.

    About this skill

    This downloadable local package turns authorized buyer-supplied AI tool-call and output logs into a fixed, reproducible review packet. It includes an installable Python CLI, a local stdio MCP adapter and a companion Agent Skill. One run creates:

    1. result.json
    2. call-matrix.csv
    3. duplicate-call-groups.csv
    4. cost-summary.csv
    5. issues.jsonl
    6. TOOL_CALL_INTEGRITY.md
    7. evidence-receipt.json

    The deterministic core joins calls to outputs by exact call ID, checks declared tool names and argument fields against a supplied catalog, detects missing and duplicate evidence, groups repeated call fingerprints and totals supplied usage costs under explicit limits. It rejects unsafe paths and malformed inputs, never overwrites an existing packet, escapes formula-active CSV cells and binds every input and output with SHA-256. Processing stays local; no API key, login, upload, telemetry or external execution is included.

    Best for AI application teams and integration consultants reviewing exported agent runs. Requires Windows 11, Python 3.11–3.14 and authorized local evidence files. Optional mcp==2.2.0 enables the local adapter.

    Limitations: no model or tool execution, trace collection, semantic output grading, token recount, vendor billing verification, retry, rollback or claim that logged actions occurred. This is a one-time local V1.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

      Free skills download straight away. Paid skills unlock right after purchase.

    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill passes our trust checks below.

    Security scanned

    Passed our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    30-day refund

    Not a fit? Get your money back

    Trust & safety

    Security scanned

    Verified clean 18 days ago

    • Passed all security checks, Safe to install

    Listed18 days ago
    Updated12 days ago

    What's inside

    Frequently Asked Questions