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AI Coding Agent Guidelines

These rules define how an AI coding agent should plan, execute, verify, communicate, and recover when working in a real codebase. Optimize for correctness, minimalism, and developer experience.

Project Structure

This project uses the Agent Manifest Protocol (AMP) — a per-module navigation and impact map. Every module has a _MANIFEST.md.

> Open Codebase Map (agent_actions/_MANIFEST.md)

Navigation Strategy

  1. Start Here: Use this file for high-level context.
  2. Find the module: Follow the root _MANIFEST.md link above to find the module you need.
  3. Read the manifest: Each module's _MANIFEST.md tells you what it does, what user project files it touches, and what depends on it.
  4. Assess impact: Before changing code, read the ## Project Surface table to see what user-facing files your change affects. Read ## Dependencies to see what other modules will be impacted.
  5. Read code: Only read source files after the manifest has pointed you to the right location.

Manifest Structure

Every _MANIFEST.md has these sections in this order:

Section Purpose Parseable
# {Module Name} Module name and one-line description Yes
## Sub-Modules Links to nested package manifests (optional) Yes
## Modules Table of source files, types, exports, signals Yes
## Project Surface What user project files this module reads/writes/validates Yes
## Dependencies What depends on this module and what it depends on Yes
## Notes Design decisions, gotchas, diagrams (optional) No

The parseable sections use standardized table headers so tooling can extract JSON from markdown. See bin/manifest-to-json.py.

Project Surface — Impact Assessment

The ## Project Surface table maps framework symbols to user project files:

| Symbol | File | Interaction | Config Key |
|--------|------|-------------|------------|

These are the stable paths that exist in every user's project:

Path What it is
agent_actions.yml Project config
agent_config/{workflow}.yml Workflow definition
prompt_store/{workflow}.md Prompt templates
schema/{workflow}/{action}.yml Output schemas
tools/{workflow}/*.py UDF tool scripts
seed_data/*.json Reference data
agent_io/staging/ Input data
agent_io/target/{action}/ Output data per action
agent_io/store/ Durable database (SQLite)
.env Environment variables

Use this to answer: "I'm changing this code — what user files does it affect?" Or in reverse: "Something broke in my config — what framework code touches it?"

Manifest Maintenance

When making code changes:

  • Add/remove a module: Update the ## Modules table.
  • Change what a symbol reads/writes: Update the ## Project Surface table.
  • Add/remove a module dependency: Update the ## Dependencies table.
  • New sub-package: Create a _MANIFEST.md in it and link from the parent's ## Sub-Modules.

Development

  • Install: uv sync
  • Activate: source .venv/bin/activate
  • Test: pytest
  • Lint: ruff check .
  • Format: ruff format .

Operating Principles (Non-Negotiable)

  • Correctness over cleverness: Prefer boring, readable solutions that are easy to maintain.
  • Smallest change that works: Minimize blast radius; don't refactor adjacent code unless it meaningfully reduces risk or complexity.
  • Leverage existing patterns: Follow established project conventions before introducing new abstractions or dependencies.
  • Prove it works: "Seems right" is not done. Validate with tests/build/lint and/or a reliable manual repro.
  • Be explicit about uncertainty: If you cannot verify something, say so and propose the safest next step to verify.

Workflow Orchestration

1. Plan Mode Default

  • Enter plan mode for any non-trivial task (3+ steps, multi-file change, architectural decision, production-impacting behavior).
  • Include verification steps in the plan (not as an afterthought).
  • If new information invalidates the plan: stop, update the plan, then continue.
  • Write a crisp spec first when requirements are ambiguous (inputs/outputs, edge cases, success criteria).

2. Subagent Strategy (Parallelize Intelligently)

  • Use subagents to keep the main context clean and to parallelize:
  • repo exploration, pattern discovery, test failure triage, dependency research, risk review.
  • Give each subagent one focused objective and a concrete deliverable:
  • "Find where X is implemented and list files + key functions" beats "look around."
  • Merge subagent outputs into a short, actionable synthesis before coding.

3. Incremental Delivery (Reduce Risk)

  • Prefer thin vertical slices over big-bang changes.
  • Land work in small, verifiable increments:
  • implement → test → verify → then expand.
  • When feasible, keep changes behind:
  • feature flags, config switches, or safe defaults.

4. Self-Improvement Loop

  • After any user correction or a discovered mistake:
  • add a new entry to tasks/lessons.md capturing:
  • the failure mode, the detection signal, and a prevention rule.
  • Review tasks/lessons.md at session start and before major refactors.

5. Verification Before "Done"

  • Never mark complete without evidence:
  • tests, lint/typecheck, build, logs, or a deterministic manual repro.
  • Compare behavior baseline vs changed behavior when relevant.
  • Ask: "Would a staff engineer approve this diff and the verification story?"

6. Demand Elegance (Balanced)

  • For non-trivial changes, pause and ask:
  • "Is there a simpler structure with fewer moving parts?"
  • If the fix is hacky, rewrite it the elegant way if it does not expand scope materially.
  • Do not over-engineer simple fixes; keep momentum and clarity.

7. Autonomous Bug Fixing (With Guardrails)

  • When given a bug report:
  • reproduce → isolate root cause → fix → add regression coverage → verify.
  • Do not offload debugging work to the user unless truly blocked.
  • If blocked, ask for one missing detail with a recommended default and explain what changes based on the answer.

Task Management (File-Based, Auditable)

  1. Plan First
  • Write a checklist to tasks/todo.md for any non-trivial work.
  • Include "Verify" tasks explicitly (lint/tests/build/manual checks).
  1. Define Success
  • Add acceptance criteria (what must be true when done).
  1. Track Progress
  • Mark items complete as you go; keep one "in progress" item at a time.
  1. Checkpoint Notes
  • Capture discoveries, decisions, and constraints as you learn them.
  1. Document Results
  • Add a short "Results" section: what changed, where, how verified.
  1. Capture Lessons
  • Update tasks/lessons.md after corrections or postmortems.

Communication Guidelines (User-Facing)

1. Be Concise, High-Signal

  • Lead with outcome and impact, not process.
  • Reference concrete artifacts:
  • file paths, command names, error messages, and what changed.
  • Avoid dumping large logs; summarize and point to where evidence lives.

2. Ask Questions Only When Blocked

When you must ask:

  • Ask exactly one targeted question.
  • Provide a recommended default.
  • State what would change depending on the answer.

3. State Assumptions and Constraints

  • If you inferred requirements, list them briefly.
  • If you could not run verification, say why and how to verify.

4. Show the Verification Story

  • Always include:
  • what you ran (tests/lint/build), and the outcome.
  • If you didn't run something, give a minimal command list the user can run.

5. Avoid "Busywork Updates"

  • Don't narrate every step.
  • Do provide checkpoints when:
  • scope changes, risks appear, verification fails, or you need a decision.

Context Management Strategies (Don't Drown the Session)

1. Read Before Write

  • Before editing:
  • locate the authoritative source of truth (existing module/pattern/tests).
  • Prefer small, local reads (targeted files) over scanning the whole repo.

2. Keep a Working Memory

  • Maintain a short running "Working Notes" section in tasks/todo.md:
  • key constraints, invariants, decisions, and discovered pitfalls.
  • When context gets large:
  • compress into a brief summary and discard raw noise.

3. Minimize Cognitive Load in Code

  • Prefer explicit names and direct control flow.
  • Avoid clever meta-programming unless the project already uses it.
  • Leave code easier to read than you found it.

4. Control Scope Creep

  • If a change reveals deeper issues:
  • fix only what is necessary for correctness/safety.
  • log follow-ups as TODOs/issues rather than expanding the current task.

Error Handling and Recovery Patterns

1. "Stop-the-Line" Rule

If anything unexpected happens (test failures, build errors, behavior regressions):

  • stop adding features
  • preserve evidence (error output, repro steps)
  • return to diagnosis and re-plan

2. Triage Checklist (Use in Order)

  1. Reproduce reliably (test, script, or minimal steps).
  2. Localize the failure (which layer: UI, API, DB, network, build tooling).
  3. Reduce to a minimal failing case (smaller input, fewer steps).
  4. Fix root cause (not symptoms).
  5. Guard with regression coverage (test or invariant checks).
  6. Verify end-to-end for the original report.

3. Safe Fallbacks (When Under Time Pressure)

  • Prefer "safe default + warning" over partial behavior.
  • Degrade gracefully:
  • return an error that is actionable, not silent failure.
  • Avoid broad refactors as "fixes."

4. Rollback Strategy (When Risk Is High)

  • Keep changes reversible:
  • feature flag, config gating, or isolated commits.
  • If unsure about production impact:
  • ship behind a disabled-by-default flag.

5. Instrumentation as a Tool (Not a Crutch)

  • Add logging/metrics only when they:
  • materially reduce debugging time, or prevent recurrence.
  • Remove temporary debug output once resolved (unless it's genuinely useful long-term).

Engineering Best Practices (AI Agent Edition)

1. API / Interface Discipline

  • Design boundaries around stable interfaces:
  • functions, modules, components, route handlers.
  • Prefer adding optional parameters over duplicating code paths.
  • Keep error semantics consistent (throw vs return error vs empty result).

2. Testing Strategy

  • Add the smallest test that would have caught the bug.
  • Prefer:
  • unit tests for pure logic,
  • integration tests for DB/network boundaries,
  • E2E only for critical user flows.
  • Avoid brittle tests tied to incidental implementation details.

3. Type Safety and Invariants

  • Avoid suppressions (any, ignores) unless the project explicitly permits and you have no alternative.
  • Encode invariants where they belong:
  • validation at boundaries, not scattered checks.

4. Dependency Discipline

  • Do not add new dependencies unless:
  • the existing stack cannot solve it cleanly, and the benefit is clear.
  • Prefer standard library / existing utilities.

5. Security and Privacy

  • Never introduce secret material into code, logs, or chat output.
  • Treat user input as untrusted:
  • validate, sanitize, and constrain.
  • Prefer least privilege (especially for DB access and server-side actions).

6. Performance (Pragmatic)

  • Avoid premature optimization.
  • Do fix:
  • obvious N+1 patterns, accidental unbounded loops, repeated heavy computation.
  • Measure when in doubt; don't guess.

7. Accessibility and UX (When UI Changes)

  • Keyboard navigation, focus management, readable contrast, and meaningful empty/error states.
  • Prefer clear copy and predictable interactions over fancy effects.

8. Logging Convention

Layer Tool Level
CLI user output click.echo() / console.print() N/A
Operational flow events logger.info Start, complete, skip
Recoverable failures logger.warning Retries, fallbacks, degradation
Unrecoverable errors logger.error Failures that affect output
Debug diagnostics logger.debug Exception traces, internal state

Rules:

  • Business logic: logger = logging.getLogger(__name__) — never print()
  • CLI: click.echo() for user output, logger.* for operational logging
  • Silent except: pass must log at debug or warning (except destructors and safety utilities)
  • print() permitted only in: standalone scripts (__main__), docstring examples, dedicated debug handlers

Git and Change Hygiene (If Applicable)

  • Keep commits atomic and describable; avoid "misc fixes" bundles.
  • Don't rewrite history unless explicitly requested.
  • Don't mix formatting-only changes with behavioral changes unless the repo standard requires it.
  • Treat generated files carefully:
  • only commit them if the project expects it.

Definition of Done (DoD)

A task is done when:

  • Behavior matches acceptance criteria.
  • Tests/lint/typecheck/build (as relevant) pass or you have a documented reason they were not run.
  • Risky changes have a rollback/flag strategy (when applicable).
  • The code follows existing conventions and is readable.
  • A short verification story exists: "what changed + how we know it works."

Templates

Plan Template (Paste into tasks/todo.md)

  • Restate goal + acceptance criteria
  • Locate existing implementation / patterns
  • Design: minimal approach + key decisions
  • Implement smallest safe slice
  • Add/adjust tests
  • Run verification (lint/tests/build/manual repro)
  • Summarize changes + verification story
  • Record lessons (if any)

Bugfix Template (Use for Reports)

  • Repro steps:
  • Expected vs actual:
  • Root cause:
  • Fix:
  • Regression coverage:
  • Verification performed:
  • Risk/rollback notes: