| name | hypothesis-tracking |
| version | 1.0.0 |
| description | Track and manage research hypotheses with confidence levels. Use when the user asks about prior research, wants to validate claims, or queries what is known about a company. |
| tools | ["get_hypotheses","save_hypothesis"] |
| resources | ["file://references/confidence_levels"] |
| metadata | {"openclaw":{"requires":{"bins":["primr-mcp"],"env":["GEMINI_API_KEY"]}}} |
Hypothesis Tracking
Primr uses a four-level confidence system: UNTESTED, VALIDATED, INVALIDATED, CONFIRMED. See references/confidence-levels.md for the full framework and lifecycle.
Operational Capabilities
Retrieve Hypotheses
get_hypotheses(company="Acme Corp")
get_hypotheses(company="Acme Corp", confidence="validated")
get_hypotheses(company="Acme Corp", topic="technology")
get_hypotheses(company="Acme Corp", include_expired=True)
Update Hypothesis Confidence
save_hypothesis(company="Acme Corp", hypothesis_id="h_001",
confidence="validated", evidence="Found AWS case study on company blog")
save_hypothesis(company="Acme Corp", hypothesis_id="h_002",
confidence="invalidated", evidence="CEO states they use Azure exclusively")
save_hypothesis(company="Acme Corp", hypothesis_id="h_001",
confidence="confirmed", evidence="Multiple sources: job posts, blog, press release")
Create New Hypothesis
save_hypothesis(company="Acme Corp", hypothesis_id="h_new_001",
claim="Company is expanding into healthcare",
confidence="untested", topic="strategy")
Expiration Rules
- Financial claims: 90 days
- Technology claims: 180 days
- Strategy claims: 365 days
- Leadership claims: no expiration
When expired hypotheses exist, query with include_expired=True, then re-validate, invalidate, or extend.
Error Handling
| Error | Resolution |
|---|
| Hypothesis not found | Verify company name and hypothesis_id |
| Duplicate ID | Use a unique hypothesis_id per company |
| Missing evidence | Always provide evidence string when changing confidence |
| Expired hypothesis | Re-query with include_expired=True to access |
Example Workflow
User: "What do we know about Acme Corp's technology?"
1. get_hypotheses("Acme Corp", topic="technology")
Results:
- [CONFIRMED] Uses microservices architecture
Evidence: CTO interview, job posts, tech blog
- [VALIDATED] AWS as primary cloud
Evidence: Job posting mentions AWS
- [UNTESTED] Considering Kubernetes migration
Evidence: None yet
2. Present to user:
"Here's what we know about Acme Corp's technology:
CONFIRMED: Uses microservices architecture
Multiple sources confirm this
VALIDATED: AWS as primary cloud
One supporting source (job posting)
UNTESTED: Considering Kubernetes migration
No evidence yet, extracted from blog speculation
Would you like me to research any of these further?"
3. If user provides new evidence:
save_hypothesis(company="Acme Corp", hypothesis_id="h_003",
confidence="validated",
evidence="User confirmed: spoke with Acme engineer at conference")
Constraints
- Unique IDs: Each hypothesis must have a unique ID per company
- Evidence Trail: Always record evidence when changing confidence
- Topic Consistency: Use consistent topic names for filtering
- Expiration Awareness: Check expiration before presenting claims
