Smart Sourcing Skill | Agent Skills

Smart Sourcing

Intelligent sourcing that requires citations only when the cost is justified by the value of verification.

Philosophy

Full sourcing is prohibitively expensive (10-16x token increase). Smart sourcing targets high-value claims where verification materially improves accuracy.

When to Source

REQUIRE Sources

| Claim Type | Example | Why Source | |------------|---------|------------| | Version numbers | "Python 3.12 added..." | Versions change, easy to verify | | Performance claims | "30% faster than..." | Quantitative claims need evidence | | Security recommendations | "Use bcrypt for..." | Security advice must be current | | API specifications | "The function accepts..." | APIs change between versions | | Release dates | "Released in Q4 2025" | Factual, verifiable | | Pricing/limits | "Free tier allows 1000 requests" | Business terms change | | Deprecated features | "X was removed in version Y" | Breaking changes need verification |

DO NOT Require Sources

| Claim Type | Example | Why No Source | |------------|---------|---------------| | General concepts | "Async improves concurrency" | Foundational knowledge | | Code examples | Demonstrative snippets | Illustrative, not factual claims | | Opinion/preference | "Consider using..." | Clearly framed as suggestion | | Common knowledge | "Git tracks changes" | Universal understanding | | Logical derivations | "Therefore, X implies Y" | Reasoning, not factual claim | | Syntax | "Use def for functions" | Language documentation is stable |

Decision Framework

Is this a factual claim?
├── No → No source needed
└── Yes → Would being wrong cause harm?
    ├── No (minor inconvenience) → No source needed
    └── Yes → Is verification cost-effective?
        ├── No (>5k tokens for low-value claim) → State uncertainty
        └── Yes → Perform web search, cite source

Implementation

Inline Citations

When sourcing is warranted:

Python 3.12 introduced `type` statement for type aliases[1].

Sources:
1. [PEP 695](https://peps.python.org/pep-0695/)

Uncertainty Markers

When sourcing isn't cost-effective but uncertainty exists:

Python 3.12 introduced the `type` statement (verify in release notes for your version).

Confidence Levels

| Confidence | Action | |------------|--------| | High (stable facts) | State directly | | Medium (may have changed) | Add verification note | | Low (uncertain) | Source or acknowledge uncertainty |

Token Cost Analysis

| Approach | Token Cost | Use Case | |----------|------------|----------| | No sourcing | Baseline | General knowledge | | Uncertainty marker | +5-10 tokens | Medium confidence | | Single source | +2-5k tokens | High-value claim | | Multiple sources | +10-20k tokens | Research tasks |

Examples

Good: Source Version-Specific Claim

User: What's new in FastAPI 0.109?

Response: FastAPI 0.109 added Pydantic v2 support as default[1] and
improved OpenAPI schema generation[2].

Sources:
1. [FastAPI Release Notes](https://fastapi.tiangolo.com/release-notes/)
2. [GitHub Release 0.109.0](https://github.com/tiangolo/fastapi/releases/tag/0.109.0)

Good: No Source for General Concept

User: How does async/await work?

Response: Async/await enables non-blocking I/O by allowing coroutines
to yield control while waiting for operations. The event loop manages
execution, resuming coroutines when their awaited operations complete.

Good: Uncertainty Marker

The connection pool default is typically 10 connections (verify in your
database driver documentation as this varies by library and version).

Integration

Works with:

conserve:response-compression - Keeps sourced responses concise
conserve:token-conservation - Weighs source cost vs value
memory-palace:knowledge-intake - Full sourcing for knowledge corpus

When To Use Full Sourcing

When NOT To Use

Internal project code that doesn't need citations
Casual conversation without factual claims

Escalate to full sourcing (accept high token cost) for:

Knowledge corpus entries (permanent documentation)
Security advisories (safety-critical)
Compliance/legal claims (audit requirements)
Research tasks (user expects thorough investigation)

For these cases, use memory-palace:knowledge-intake workflow which is designed for thorough sourcing.

Exit Criteria

[ ] Every claim categorized as requiring a source (version numbers, performance claims, security recommendations, API specs, release dates, pricing/limits, deprecated features) has an inline citation or a verification note
[ ] No web search performed for claims categorized as general concepts, code examples, opinions, common knowledge, logical derivations, or stable syntax
[ ] Claims with medium confidence carry an explicit uncertainty marker (e.g., "verify in release notes for your version") rather than being stated as fact or sourced at high token cost
[ ] Decision tree applied: factual claim → harm if wrong → verification cost-effective → source; each branch followed explicitly for claims exceeding medium confidence

Agent Skills: Smart Sourcing

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