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aoci_update_entry

Write one complete machine-issued Entry batch through validated Impact, Diff, CAS, AtomicWrite, and Recovery pipeline while preserving batch and candidate identities.

Instructions

Write one complete current machine-issued model-authored Entry batch through the existing Impact, projected validation, Diff, CAS, AtomicWrite, Baseline/Database Binding, Receipt, Ledger, and Recovery pipeline. For Volumes Code authoring, preserve the exact code_batch_id, every candidate_id, path, and source_sha256 returned by no-argument aoci_maintain: aoci_update_entry.code_batch_id must equal code_plan.batch_id and every returned Code candidate.batch_id; authoring_batch.batch_identity is a different cross-domain envelope identity and must never be used in code_batch_id. Database candidates preserve the exact top-level batch_id and every candidate_id; never copy Database Volume or Table Evidence hashes into source_sha256. max_entries limits this request and atomic transaction only, not the logical plan, Whole-Index, or Managed Scope. The submitted entries must be the complete candidate set for the current machine-issued batch; the Host must not slice Maintain output. AOCI validates all candidates and source/Evidence, Scope, Composite, tag, FRAS, R/S form, and projected budget bindings before writing Code at most once, Database at most once, and Baseline/Binding at most once. R is model-authored semantics: AOCI never checks one Entry's relations against another Entry, so a relation naming an unwritten, unmanaged, or ambiguous target is accepted and persisted exactly as written and never causes a replan; author R freely and never delete or rewrite it to satisfy the machine. A successful batch with remaining nonzero is not Whole-Index aligned: call Maintain again against the new preimage and continue. A repair_required response returns every deterministic Finding with candidate_index, canonical_object_identity, rule_code, and safe_repair_action; repair only retry_scope and resubmit the same complete current batch. Existing direct single-object, Legacy, and compatible Code source_sha256 inputs remain supported. Root and Meta are Guard-only. Never guess, reduce Scope for transport limits, or submit a partial machine-issued batch.

Input Schema

NameRequiredDescriptionDefault
pathNoRepository-relative target path for compatibility single-Entry mode
entriesNoSubmit the complete candidate set for the current machine-issued batch; continue through Maintain when remaining is nonzero
batch_idNoMachine-owned complete current Database Cognition batch identity returned by aoci_maintain
new_entryNoComplete single-line Entry for compatibility single-Entry mode
object_refNoCanonical Database object identity for compatibility single-Entry mode
candidate_idNoMachine-owned Code or Database Cognition candidate identity returned by aoci_maintain; do not synthesize it or copy Evidence hashes into it
code_batch_idNoExact code_plan.batch_id returned by aoci_maintain; it equals every returned Code candidate.batch_id. Never use authoring_batch.batch_identity here
source_sha256NoCompatibility binding for Code source bytes or an existing Database object update; Database Cognition authoring uses candidate_id and batch_id instead

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and discloses substantial detail: validation happens before writes, Code/Database/Baseline/Binding are each written at most once, R relations are persisted literally without replanning, and repair_required returns deterministic findings with named fields. It still does not describe permissions/auth, concurrency behavior, or the normal success response shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core action is front-loaded, and most sentences contain domain-specific constraints rather than filler. However, the description is a long, dense paragraph with repeated warnings and nested clauses, making it harder to scan than necessary for an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex write tool with no annotations, no output schema, and eight parameters, the description is largely complete: it explains the pipeline, identity preservation, validation, repair behavior, and continuation through Maintain. It is less complete on normal response shape and on the unexplained max_entries reference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds meaningful cross-parameter semantics: code_batch_id must equal code_plan.batch_id and candidate batch_id, candidate_id and source_sha256 must be preserved exactly, and entries must be the complete candidate set. One issue is that max_entries is discussed even though it is not present in the input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific write action: submit one complete machine-issued Entry batch through the existing validation and write pipeline. It also distinguishes this tool from aoci_maintain by tying submission to Maintain output and continuation. The purpose is clear but buried under dense internal jargon like 'Impact, projected validation, Diff, CAS, AtomicWrite, Baseline/Database Binding, Receipt, Ledger, and Recovery pipeline.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit operational context: use code_batch_id from no-argument aoci_maintain, call Maintain again when remaining is nonzero, and resubmit the same complete batch after repair_required. It also states when not to use it for partial submissions and notes compatibility single-object/Legacy modes. It does not, however, explicitly route the agent to aoci_remove_entry or other siblings for alternative operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.