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shiplog currently describes itself as a GitHub-backed knowledge graph with optional memory-store integration, but its documented retrieval workflow is still too abstract. The current guidance says to search issues, PRs, commits, envelopes, and optional memory, but it does not define a clear retrieval order that gives the agent a cheap map before deeper reads.
The user supplied a design pattern from napkin: give the agent a terrain map first, run lexical search with visible match reasons, and treat native links as the graph instead of depending on embeddings or a vector store.
Design Summary
Keep shiplog retrieval GitHub-native and explicit rather than relying on vector-memory rhetoric.
Define a progressive-disclosure retrieval loop: map first, lexical search second, edge-following third, full-thread reads last.
Use existing Shiplog structures as the graph: issue numbers, PR references, branch names, stacked markers, envelope fields, and timeline tags.
Keep ork:remember / ork:memory optional and clearly secondary to the GitHub-native retrieval path.
Approach
Document a retrieval playbook that maps the napkin pattern onto Shiplog's existing primitives:
Build a terrain map from open issues, PRs, labels, titles, branch names, and latest state/history envelopes.
Run lexical search over issues, PRs, commits, and local repo docs before trying any optional memory layer.
Show why a result matched by surfacing headings or matching lines from the top hits before reading full threads.
Follow native edges such as #42, Closes #42, Addresses #42, [stack: #N], issue/<id>-..., and envelope references like issue, pr, supersedes, and amends.
Treat optional memory stores as an add-on for recall, not the default explanation of how Shiplog retrieval works.
Alternatives Considered
Keep the current "knowledge graph" language unchanged: too vague about retrieval behavior, and it invites people to assume embeddings or hidden memory infra are central.
Add a brand-new retrieval backend to Shiplog: out of scope for this repo, which is primarily a workflow/skill package.
Drop optional memory integration entirely: unnecessary; the real fix is making the default retrieval path explicit and cheap.
Sources and Verification Status
[verified] Napkin publicly describes a markdown-on-disk retrieval pattern centered on overview, lexical search, and wiki-link navigation.
Checked: The project describes local markdown retrieval, an overview/map concept, lexical search behavior, and native link traversal.
[unverified] Benchmark figures supplied by the user for HotpotQA, including exact recall and F1 numbers.
Why unverified: I have not located a primary-source benchmark artifact in the upstream materials during this planning pass.
Next step: Verify the evaluation script or published benchmark notes before citing any numeric claims in Shiplog docs.
Tasks
T1: Rewrite Phase 6 retrieval guidance around progressive disclosure[tier-3]
What: Update skills/shiplog/SKILL.md so Phase 6 explicitly defines a map-first, lexical, edge-following retrieval loop and positions optional memory as secondary.
Files:skills/shiplog/SKILL.md (modify)
Allowed to change: Phase 6 text, nearby retrieval wording that directly supports the new workflow
Must not change: Unrelated phases, branch/PR/review rules, or label semantics
Forbidden judgment calls: Do not introduce new product capabilities that are not documented elsewhere in the repo
Stop and ask if: The change would require adding new commands or non-doc code that is not already in scope
Verification: Read the updated phase and confirm the retrieval order is explicit, bounded, and consistent with artifact envelopes
Return artifact: Diff summary for skills/shiplog/SKILL.md
Decision budget:none
Accept when: A reader can tell what to do first, second, and third when looking up history
Context: This is the workflow definition that all other docs should align to
T2: Update /shiplog lookup to show match reasons and edge-following[tier-3]
What: Revise commands/shiplog/lookup.md so it tells the agent to build a terrain map, inspect top hits for matching lines/headings, and follow native Shiplog edges before deep reading.
Files:commands/shiplog/lookup.md (modify)
Allowed to change: Task steps and output format for lookup
Must not change: Command purpose or Shiplog phase numbering
Forbidden judgment calls: Do not pretend the command already has BM25 or vector-search capabilities
Stop and ask if: The command needs tooling that cannot be expressed with gh, git, and read access
Verification: Read the command top-to-bottom and confirm it describes a coherent operator loop
Return artifact: Diff summary for commands/shiplog/lookup.md
Decision budget:none
Accept when: The command tells the operator not just what matched, but why and what to follow next
Context: This is where the map-first pattern becomes user-visible
T3: Reposition README retrieval claims around explicit maps instead of hidden memory infrastructure[tier-3]
What: Update README.md so the retrieval story emphasizes progressive disclosure, GitHub-native links, and low-cost lookup before optional memory integrations.
Files:README.md (modify)
Allowed to change: Retrieval-related feature copy, command descriptions, and companion-skill wording tied to memory
Must not change: Installation instructions, unrelated feature descriptions, or the existing testimonial section unless needed for consistency
Forbidden judgment calls: Do not cite unverified benchmark numbers or claim Shiplog ships BM25/TF-IDF today
Stop and ask if: The README change requires a broader product-positioning rewrite outside retrieval
Verification: Read the edited sections and confirm they do not overclaim implementation details
Return artifact: Diff summary for README.md
Decision budget:none
Accept when: The README makes the retrieval philosophy legible without suggesting a vector backend
Context: The public-facing message should match the actual documented workflow
Open Questions
Should Shiplog introduce a dedicated overview or map command later, or is hunt enough as the top-level terrain map?
Should native edge-following be documented only in Phase 6, or also called out in resume/start flows?
Is the phrase "knowledge graph" still worth keeping as a metaphor if the docs now emphasize lexical retrieval and explicit references?
Context
shiplog currently describes itself as a GitHub-backed knowledge graph with optional memory-store integration, but its documented retrieval workflow is still too abstract. The current guidance says to search issues, PRs, commits, envelopes, and optional memory, but it does not define a clear retrieval order that gives the agent a cheap map before deeper reads.
The user supplied a design pattern from napkin: give the agent a terrain map first, run lexical search with visible match reasons, and treat native links as the graph instead of depending on embeddings or a vector store.
Design Summary
ork:remember/ork:memoryoptional and clearly secondary to the GitHub-native retrieval path.Approach
Document a retrieval playbook that maps the napkin pattern onto Shiplog's existing primitives:
#42,Closes #42,Addresses #42,[stack: #N],issue/<id>-..., and envelope references likeissue,pr,supersedes, andamends.Alternatives Considered
Sources and Verification Status
[verified]Napkin publicly describes a markdown-on-disk retrieval pattern centered onoverview, lexical search, and wiki-link navigation.[unverified]Benchmark figures supplied by the user for HotpotQA, including exact recall and F1 numbers.Tasks
T1: Rewrite Phase 6 retrieval guidance around progressive disclosure
[tier-3]skills/shiplog/SKILL.mdso Phase 6 explicitly defines a map-first, lexical, edge-following retrieval loop and positions optional memory as secondary.skills/shiplog/SKILL.md(modify)skills/shiplog/SKILL.mdnoneT2: Update
/shiplog lookupto show match reasons and edge-following[tier-3]commands/shiplog/lookup.mdso it tells the agent to build a terrain map, inspect top hits for matching lines/headings, and follow native Shiplog edges before deep reading.commands/shiplog/lookup.md(modify)gh,git, and read accesscommands/shiplog/lookup.mdnoneT3: Reposition README retrieval claims around explicit maps instead of hidden memory infrastructure
[tier-3]README.mdso the retrieval story emphasizes progressive disclosure, GitHub-native links, and low-cost lookup before optional memory integrations.README.md(modify)README.mdnoneOpen Questions
overviewormapcommand later, or ishuntenough as the top-level terrain map?Authored-by: openai/gpt-5.4 (codex)