Stg Extracting Insights

Insight Extraction

Process governor-provided expert sources into structured, tier-labeled insights. Every extracted claim carries a tier label and maps to a specific hypothesis. Behavioral vs hypothetical evidence distinction maintained throughout.

Procedure

Step 1: Ingest Source [S]

Read: source URL, file, or transcript (governor-provided).

• If URL: WebFetch to retrieve content.
• If file: Read file content.
• If transcript: Read transcript.

Identify structure (chapters, sections, speakers). Capture metadata: date, author, platform, publication context.

Produce: raw content + metadata.

Gate: source_ingested: bool -- content retrieved, metadata captured (date, author).

• Pass: Step 2.
• Fail: If URL returns error, report to governor. If content is gated/paywalled, report: "Cannot access -- governor must provide content directly."

Step 2: Extract Claims and Frameworks [K-grounded]

Grounded in: raw content from Step 1.

Identify and extract:

| Category | What to Look For | Example | |----------|-----------------|---------| | Frameworks | Mental models, decision structures | "The 4 properties of a good problem" | | Principles | Universal rules, guidelines | "Never price below 10x the cost of the alternative" | | Tactics | Specific actions, playbooks | "Use 5-second tests to validate landing page messaging" | | Data points | Benchmarks, metrics, statistics | "Average PLG conversion rate is 3-5%" | | Warnings | Anti-patterns, failure modes | "Teams that skip problem validation fail 3x more often" |

For each: state the claim, cite the specific quote or passage (with location/timestamp if applicable), note the context.

Produce: extracted claims list.

Gate: claims_extracted: bool -- at least 3 claims extracted, each with specific citation from source.

• Pass: Step 3.
• Fail: If source is too thin for 3 claims, extract what exists and note: "Source produced limited actionable claims."

Step 3: Tier-Label Each Claim [R]

For each claim, apply the operational test: "What new data would I need to see to change my mind about this?"

| Answer | Tier | Example | |--------|------|---------| | "None -- this is definitional or from cited data" | T1 | "SaaS gross margins are typically 70-85%" (from benchmark report) | | "Validate the reasoning chain" | T2 | "Teams with this problem spend 40% of time on workarounds" (expert estimate) | | "Customer/market data I don't have" | T3 | "Customers will pay 10x for this solution" (expert opinion about WTP) |

Also distinguish:

• Behavioral evidence: "We observed X happen" -- stronger
• Hypothetical evidence: "X should work because Y" -- weaker

Produce: tier-labeled claims.

Gate: claims_labeled: bool -- every claim has tier label and behavioral/hypothetical classification.

• Pass: Step 4.
• Fail: Claims without clear tier are likely T2 or T3. Default to T2 for reasoning, T3 for predictions.

Step 4: Map to Hypotheses [R]

For each claim, determine which hypothesis it supports or challenges:

| Mapping Target | Evidence About | |---------------|---------------| | Problem hypothesis | Pain existence, frequency, severity, alternatives | | Segment hypothesis | Who has the problem, observable characteristics | | Unit Economics hypothesis | Pricing, costs, conversion rates, benchmarks | | Solution Design | Features, growth architecture, MVP approach, positioning, differentiation, jobs-to-be-done | | General | Domain knowledge, not hypothesis-specific |

Explicitly search for claims that contradict current register. Challenging evidence is more valuable than confirming evidence.

Produce: hypothesis-mapped claims.

Gate: claims_mapped: bool -- every claim mapped to at least one hypothesis or marked "General."

• Pass: Step 5.
• Fail: If all claims map to "General," the source may not be relevant to current strategy work. Report to governor.

Step 5: Write Outputs [S]

For hypothesis-specific insights: format as EvidenceItems:

• [{TYPE: WEB_RESEARCH or OBSERVATION}] [{T1|T2|T3}] {date} -- {source}: {detail}
• Note which hypothesis they should be added to

For general insights: write to knowledge/ as standalone file if source is broadly relevant.

The agent integrates evidence items into the register on the next BUILD/CHALLENGE pass.

Produce: evidence items for register integration + optional knowledge file.

Gate: outputs_written: bool -- evidence items formatted for register integration, each with hypothesis target.

• Pass: Done.
• Fail: Ensure every output has the required format fields: type, tier, date, source, detail.

Quality Criteria

• Every extracted claim cites specific passage from source (not paraphrased without reference)
• Tier labels applied to every claim with justification
• Behavioral vs hypothetical distinction maintained (quotes about what happened vs what should happen)
• Claims mapped to specific hypotheses (not all dumped as "general")
• Source metadata complete (date, author, URL if applicable)

Failure Modes

| Mode | Signal | Recovery | |------|--------|----------| | Uncritical extraction | All claims extracted as T1 or all labeled as important | Apply tier test rigorously. Expert opinion about what customers want is still T3. Expert frameworks are T2. Only cited data is T1 | | Confirmation bias in extraction | Only insights supporting existing hypotheses extracted; challenging insights omitted | Explicitly search for claims that contradict current register. Challenging evidence is more valuable than confirming evidence | | Quote without context | Extracted quote is stripped of qualifying language that changes its meaning | Include surrounding context. "This works" may have been preceded by "In enterprise markets above $50K ACV" -- the qualifier matters |

Boundaries

In scope: Source ingestion (URL, file, transcript), claim extraction (frameworks, principles, tactics, data points, warnings), tier labeling, behavioral/hypothetical classification, hypothesis mapping, evidence item formatting.

Out of scope: Autonomous web research (strategist does this directly), competitive analysis (stg-analyzing-competition), market sizing (stg-sizing-markets), hypothesis construction (skills handle their own domains).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: BellaBe
• Source: BellaBe/strategy-os
• License: MIT
• Homepage: https://bellabe.github.io/leanos/

Install and usage instructions live in the source repository linked above.