Files
Bo 3213afcf1c Default to native execution and report independently accepted work (#1129)
## Change

Make native coding-agent execution the default AgentOps entry path with
zero mandatory skills. Preserve full bundles and add repeatable `ao
skills link --skill NAME` selection, validating the entire selection
before writes. Align product, installation, architecture and generated
command documentation.

Extend the existing trial readout to separate endpoint test results,
execution state and independently accepted work. Bind supplied judgments
to exact content, acceptance and native evidence. Reject empty
implementation subjects and require the caller's complete criterion ID
set before reporting acceptance. Preserve genuine nonempty and
deletion-only subjects, valid failures and missing-proof outcomes.

## Validation

- Native onboarding from empty home/consumer directories produces no
setup files; selective/full linking and failure boundaries are covered.
- Actual RED/GREEN regressions cover empty subjects and the
partial-criterion omission found by independent review.
- Full Go build, vet and race/shuffle tests; affected Go lint; 88 Python
readout/statistics tests passed.
- All 73 gates, generated projections, strict documentation build and
local aggregate passed (10 passed; one documented optional absence).
- All nine PR checks succeeded at
`7df0d42b12f35ffc22008cc10a40339afcfbb6a0`.
- Fresh author-distinct review passed all six acceptance criteria over
all 59 changed paths, with no findings or unchecked scope, after
repairing the criterion-coverage finding.

## Evidence limits

The real native coding repair demonstrates usability, not comparative
skill uplift. The strict live-session machine replay remains NOT_PROVEN
where execution/identity observations are unavailable; the source review
PASS is retained separately. Existing cohort limits and the historical
aggregate-enforcement gap remain unwaived. No new comparative cohort,
scheduler, skill-corpus deletion, memory migration or global
installation is included.
2026-09-10 20:28:22 +00:00
..

Role-Based Profiles

Purpose: Organize 12 domain skills into 3 discoverable profiles for different work contexts.

Version: 3.3.0 (Updated for skills-based approach)


How to Use Profiles

Profiles are documentation groupings, not executable configs. They organize AgentOps skills by domain so you can quickly find which skills are relevant to your work.

AgentOps 3.0 workflow recipes such as product-council, engineering-team, and always-on-substrate were documented in Activation Profiles (historical reference; retired path: ../activation-profiles.md). Activation profiles are product recipes with explicit inputs, commands, and expected artifacts; this page remains the role taxonomy.

To use a profile:

  1. Find your domain in the table below
  2. Open the profile YAML (e.g., docs/profiles/roles/software-dev.yaml) to see which skills it groups together
  3. Use those skills directly via slash commands (/research, /plan, /implement) or by reading the SKILL.md files listed in the profile

You do not "load" or "activate" a profile — you read it to discover which skills apply to your workflow, then invoke those skills individually.


Quick Start

You're doing... Profile Key Skills
Building apps (APIs, frontends, features) software-dev languages, development, code-quality
Operations (incidents, monitoring, deploys) platform-ops operations, monitoring, security
Writing (docs, research, patterns) content-creation documentation, research, meta

The 3 Profiles

1. Software Development (software-dev)

What you do:

  • Build applications (backend APIs, frontends, full-stack)
  • Write code in Python, Go, Rust, TypeScript, Java
  • Review code and generate tests
  • Deploy with CI/CD pipelines

Skills included:

Skill Knowledge Areas
languages Python, Go, Rust, Java, TypeScript, Shell (6)
development Backend, frontend, fullstack, mobile, iOS, deployment, AI, prompts (8)
code-quality Review, improve, test generation (3)
validation Assumptions, continuous, planning, tracer bullets (4)
data Engineering, science, ML, MLOps (4)

Example workflow:

1. /research "API design for user auth"
2. Load languages skill for Python patterns
3. Load development skill for backend architecture
4. Load code-quality skill before commit

2. Platform Operations (platform-ops)

What you do:

  • Respond to production incidents
  • Monitor system health and performance
  • Debug errors and analyze logs
  • Manage deployments and infrastructure

Skills included:

Skill Knowledge Areas
operations Incident response, triage, postmortems, error detection (4)
monitoring Alerts/runbooks, performance engineering (2)
security Penetration testing, network engineering (2)
validation Assumptions, tracer bullets (4)
meta Context, execution, autonomous work (6)

Example workflow:

1. Alert fires → Load operations skill
2. Check metrics → Load monitoring skill
3. After resolution → Load meta skill for postmortem

3. Content Creation (content-creation)

What you do:

  • Write documentation (technical and non-technical)
  • Extract patterns from completed work
  • Conduct research and analysis
  • Create tutorials and examples

Skills included:

Skill Knowledge Areas
documentation Create, optimize, Diátaxis audit, API docs (4)
research Code, docs, history, archive, structure, specs (6)
meta Context, observer, memory, retro analysis (6)
specialized Accessibility, support, UX (6)

Example workflow:

1. /research "authentication patterns in our codebase"
2. Load research skill for exploration
3. Load documentation skill for writing
4. Load meta skill for retrospective

Skills by Profile

Skill software-dev platform-ops content-creation
languages
development
documentation
code-quality
research
validation
operations
monitoring
security
data
meta
specialized

Loading Skills

Skills load into main context with full tool access:

# Read a skill directly
Read skills/languages/SKILL.md

# Or let triggers auto-load
"I need help with Python async patterns"
# → languages skill auto-activates

Profile Files

profiles/
├── README.md                    # This file
├── roles/
│   ├── software-dev.yaml        # Software development profile
│   ├── platform-ops.yaml        # Platform operations profile
│   └── content-creation.yaml    # Content creation profile
└── examples/
    ├── software-dev-session.md  # Example dev session
    ├── platform-ops-session.md  # Example ops session
    └── content-creation-session.md  # Example writing session