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Hypothesis Tracking Blisspixel Primr

ASecurity

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.

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  • Added September 2, 2026
ai-agentskubernetesawsazureapi

Works with

  • api
  • mcp

Security analysis

A100/100

Scanned September 2, 2026

npx -y skills add majiayu000/claude-skill-registry --skill hypothesis-tracking-blisspixel-primr --agent claude-code

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SKILL.md
---
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

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