Issue Index
All Issues
Complete comprehensive list of all issues.
Nested Fields Do Not Match
The AI returns nested structured fields whose internal shape, hierarchy, parent-child relationship, or contained values do not match the expected structure.
No Owner for Agent Action
An agent action can affect the system without a declared responsible owner, authority, or accountable decision path.
Old Output Expectations Survive Migration
Expectations from a prior model, prompt, schema, tool, or workflow survive a migration and continue shaping review or downstream handling after they should be replaced.
One Prompt Carries Too Many Meanings
A single prompt carries too many meanings, goals, roles, constraints, or implied tasks for the AI to interpret consistently.
Output Breaks After Model Change
Output that previously worked begins failing after a model, mode, runtime, or product behavior changes.
Output Breaks the Next Step
The AI output looks acceptable by itself but cannot be used by the next tool, workflow step, parser, reviewer, or downstream consumer.
Output Changed Without Declared Change
Output shape, content, format, fields, or behavior changes without a declared change to the prompt, schema, model, workflow, or governing rule.
Output Exceeds Length Limit
The AI output exceeds a declared length, token, word, character, section, field, or size limit.
Parallel Reviews Never Agree
Parallel AI, human, workflow, or tool reviews keep producing different results without resolving into a shared decision state.
Permissions Conflict After Being Combined
Permissions, approvals, roles, policies, or authority rules that seem valid separately conflict when combined in the same workflow or AI action.
Policy Area Has No Examples
A policy, rule, standard, or guidance area has no examples showing how it should apply to real cases.
Policy Decision Depends on Itself
A policy decision requires the outcome of the same policy decision before it can be made.
Policy Exception Spreads Too Far
A narrow policy exception, allowance, or special case spreads beyond its intended scope and begins governing broader cases.
Policy Update Not Reflected in Output
A policy, rule, standard, or instruction has been updated, but the AI output still follows the older version.
Prompt Behavior Changed Without Version Change
A prompt begins producing different behavior even though no prompt version, model version, workflow version, or declared dependency change is recorded.
Prompt Changed but Workflow Did Not
A prompt changes but the workflow, parser, review step, routing rule, or downstream expectation still assumes the old prompt behavior.
Prompt Does Not Say What to Exclude
The prompt declares what to include but does not declare what should be excluded, allowing unwanted scope, sources, content, or actions into the result.
Prompt Has Too Many Valid Interpretations
The prompt allows too many reasonable interpretations, causing the AI to choose among valid paths without enough guidance.
Prompt Only Works After Retry
The prompt fails, misroutes, or produces an unusable response on one attempt but works after retry without a meaningful change to the input.
Relationship Map Has Missing Links
A map of related Issues, rules, patterns, cases, fields, tools, or workflow steps is missing links needed to navigate or reason over the structure.
Repair Step Created New Breakage
A repair, correction, retry, or fix step addresses one problem but introduces a new failure elsewhere.
Repeated Constraints Create Confusion
Repeated constraints, instructions, limits, or exclusions make the task harder to interpret instead of clearer.
Results Vary Too Much
Repeated or comparable runs produce outputs that vary more than the task, workflow, or user can tolerate.
Retrieval Exceeds Evidence Limit
The AI retrieves, uses, cites, or considers more evidence than the task permits or more than the review surface can support.