Context Gather

Context Gather

Collect multi-source context before planning or implementation. Searches Serena, Context7, DeepWiki, and web sources, then returns a focused summary that downstream commands can detect and skip redundant fetches.

Model choice (behavior change from prior /context-gather slash command): this skill declares model: claude-sonnet-4-6, downgraded from the slash command's opus. Context retrieval is search-and-synthesis work, not deep reasoning; the cost-appropriate tier per ADR-002 model selection is sonnet. Skill behavior is otherwise unchanged.

Triggers

Quick Reference

When to Use

Use this skill when:

• Starting a complex task that needs multi-source context before planning or implementation.
• A lifecycle command (/build, /plan, /research) triggers preflight context loading.
• You need to pull framework-specific guidance from Context7 alongside project memory.
• Exploring what the memory tiers already record about a topic before committing to an approach.

When to Skip

Skip this skill when:

• A CONTEXT_LOADED: <topic> marker for the same topic already exists in the current conversation. Do not re-fetch.
• The task is trivial and single-step (no external context needed).
• You already have sufficient context from a prior skill invocation or manual research.
• The topic is purely internal to the current file (no cross-cutting concerns).

Process

Phase 1: Check for Prior Invocation

1. Scan the current conversation for an existing CONTEXT_LOADED: marker line.
2. If a marker exists whose topic matches the current request, report "Context already loaded for " and stop. Do not re-fetch.

Phase 2: Search Across Knowledge Tiers

Follow references/context-retrieval.md for the source-priority strategy, the untrusted-content guard, and the synthesis and citation discipline.

1. Search the following tiers, in parallel where possible:
   • Serena Memory: Always first. Read this project's memories for prior decisions, patterns, and ADRs on the topic.
   • Context7: Query framework-specific documentation if the topic involves a known library or SDK.
   • DeepWiki: Read repository-level documentation for relevant GitHub repos.
   • Web Search: Fall back to web sources only when memory and docs are insufficient.
2. Stop early once the queried tiers give sufficient coverage for the request.
3. For each tier actually queried, emit a marker line:

TIER_QUERIED: <tier>

Where <tier> is one of: serena, context7, deepwiki, web. Emit one TIER_QUERIED: line per tier actually queried.

Phase 3: Synthesize, Emit Marker, and Return

1. Combine findings into a focused summary. Include:
   • Relevant code snippets and file paths.
   • Architectural insights and ADR references.
   • Framework-specific guidance (if applicable).
   • Gaps or unknowns that remain.
2. Emit the marker line at the end of the summary output:

CONTEXT_LOADED: <topic>

Where <topic> is a short, normalized label for the subject (e.g., pytest-fixtures, session-protocol, react-server-components).

3. Return the summary and marker to the calling command or user. Downstream callers (/build, /plan, /research per SPEC-005) detect the marker and skip redundant context fetches.

Extension Points

1. Additional knowledge tiers: new MCP servers (e.g., a future code-search server) slot into Phase 2 without changing the skill structure.
2. Marker protocol: the CONTEXT_LOADED: format can be extended with metadata (e.g., CONTEXT_LOADED: <topic> [tier=serena,context7]) to convey which sources were queried.

Tools

This skill searches the knowledge tiers using:

• mcp__serena__read_memory, mcp__serena__list_memories
• mcp__context7__resolve-library-id, mcp__context7__get-library-docs
• mcp__deepwiki__read_wiki_structure, mcp__deepwiki__read_wiki_contents, mcp__deepwiki__ask_question
• WebSearch, WebFetch

Anti-Patterns

Verification

After execution, confirm:

• Reconciliation (fetch path only): grep -c '^TIER_QUERIED:' <output> >= 1, with one TIER_QUERIED: <tier> line per source actually queried. Exempt when the skill short-circuited on a prior CONTEXT_LOADED: marker (no tiers queried) or early-stopped after one source gave sufficient coverage.
• Summary addresses the stated topic with specific findings, not generic advice.
• CONTEXT_LOADED: <topic> marker line is present at the end of output.
• No raw tool output was returned; findings are synthesized.
• If a prior marker existed for the same topic, the skill short-circuited without re-fetching.

References