Missing Recommendation Axes
May 3, 2026 · View on GitHub
Companion note · Addresses GitHub issue #4
Context
clawfit's README frames it as an agent + LLM + hardware recommendation engine. The current recommendation pipeline filters and scores on:
task(qa, code-gen, research, summarization, classification, data-analysis)latency(low / medium / high)budget(cost_per_1k_tokens threshold)network(online / offline)hardware(laptop / workstation / cloud)statefulness(stateless / session / persistent)
These axes are well-suited to the current registry (4 agents, 10 LLMs, 5 hardware). However, as the registry grows and more org profiles emerge, several important axes are not yet modeled.
Missing axis 1 — Model/provider trust and governance
Gap: A network: online recommendation currently treats all cloud providers as equivalent. But for many orgs, provider identity is a hard constraint.
| New dimension | Values | Example constraint |
|---|---|---|
provider_trust | open_weight / commercial_api / managed_gov | "we only use open-weight models" |
data_residency | ISO country code list | "data must not leave EU" |
audit_trail | none / basic / soc2 / hipaa | compliance requirement |
model_license | mit / apache2 / cc_by / proprietary | legal/IP policy |
Where it lives: llms.json registry entries + a new governance_profile filter in filters.py.
Recommended v0.4 addition:
"license": "mit",
"data_residency": ["global"],
"audit_trail": "none"
Missing axis 2 — Deployment / ops complexity
Gap: The current model assumes the user can install and run whatever is recommended. In practice, setup_complexity is a hard constraint for many teams.
| New dimension | Values | Example constraint |
|---|---|---|
setup_complexity | zero / low / medium / high | "we can't run local Docker" |
managed_service | true / false | fully managed vs self-hosted |
multi_user | true / false | single-developer vs team deployment |
Where it lives: agents.json registry entries.
Example:
- Claude Code:
setup_complexity: low,managed_service: true,multi_user: false - OpenHands self-hosted:
setup_complexity: medium,managed_service: false,multi_user: true - vLLM serving stack:
setup_complexity: high,managed_service: false,multi_user: true
Missing axis 3 — Agent autonomy level
Gap: The current taxonomy doesn't distinguish between interactive agents (user approves each step) and fully autonomous agents (fire-and-forget). These require different governance postures.
| Autonomy level | Description | Examples |
|---|---|---|
interactive | All actions require user approval | Cursor (ask mode), Continue |
supervised | Runs autonomously, reports checkpoints | Claude Code default |
autonomous | Runs until done; human reviews output | Claude Code Routines, Twill.ai |
swarm | Multiple autonomous agents coordinate | DureClaw, OpenHands multi-agent |
Where it lives: agents.json as autonomy_level field.
Missing axis 4 — Task taxonomy expansion
Gap: Current tasks are: qa, code-gen, research, summarization, classification, data-analysis. Several high-signal use cases are not covered:
| Missing task | Evidence | Proposed tag |
|---|---|---|
| Security testing | Shannon, Strix (both in L1) | security-testing |
| Voice/dictation coding | Superwhisper (in registry) | voice-coding |
| Document automation | craft-agents-oss (L6) | document-automation |
| Financial analysis | TradingAgents, ai-hedge-fund (L1/L2) | financial-analysis |
| Media production | HyperFrames signal (04-29 scan) | media-production |
| Legal research | korean-law-mcp (in registry) | legal-research |
When to add: When at least 2 independent tools in the registry share the same task type AND a real org profile generates a recommendation request for it.
Current recommended action: Add security-testing now (Shannon + Strix are both in L1 registry). Defer others until registry density supports them.
Missing axis 5 — Team/org profile dimensions
Gap: The current model has no explicit team-size or org-maturity filters. Scoring implicitly handles this via agent metadata but the filter layer doesn't expose it.
| New dimension | Values | Use |
|---|---|---|
team_size | solo / small / medium / large | Affects multi-user, governance needs |
org_maturity | 1-7 scale | From "no agents yet" to "automated fleet" |
primary_role | developer / researcher / exec / ops | Tunes scoring weights |
Where it lives: User-facing clawfit profile questionnaire inputs, not in registry JSON.
Recommended implementation sequence
| Priority | Axis | Effort | Value |
|---|---|---|---|
| 1 | security-testing task | Low — add to Shannon + Strix | Closes a clear gap |
| 2 | setup_complexity on agents | Medium — add to all 4 agents | Filters out impractical recommendations |
| 3 | autonomy_level on agents | Low — metadata only | Enables governance-aware filtering |
| 4 | model_license + audit_trail on LLMs | Low — metadata only | Unlocks enterprise filtering |
| 5 | governance_profile filter in filters.py | Medium — code change | Connects metadata to recommendations |
| 6 | team_size / org_maturity in profile | High — UX change | Enables personalized scoring |