How do I install the Cross Ref Topic Ledger skill?

Run npx skillmds add lyndonkl/cross-ref-topic-ledger in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Cross Ref Topic Ledger safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Cross Ref Topic Ledger?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Cross Ref Topic Ledger free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Cross Ref Topic Ledger?

lyndonkl (@lyndonkl) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Cross Ref Topic Ledger by lyndonkl — Agent Skill

Name: Cross Ref Topic Ledger
Rating: 4.5 (4 reviews)
Author: lyndonkl

Cross Ref Topic Ledger

For each Trend Scout candidate item, checks substacker shared-context/topic-ledger.md and tags with NEW | OVERLAPS seed:{slug} | OVERLAPS draft:{slug} | OVERLAPS published:{slug}. Adds a reinforcement_angle note for items overlapping with published posts ("external confirmation of X"). Read-only against the ledger. Use after summarize-signal, before rank-by-user-fit. Trigger keywords — cross-ref, ledger check, overlap, reinforcement, dedup external.

lyndonkl 6c188c4 2.4 KB Updated Sep 9, 2026

File contents

Cross-Ref Topic Ledger

Workflow

Per candidate:
- [ ] Step 1: Parse topic-ledger.md into {slug, title, status, tags, last_touched} records
- [ ] Step 2: Extract 2-5 topic tags from the candidate's summary (reuse ledger vocabulary)
- [ ] Step 3: Match candidate to ledger entries by tag overlap (≥2 shared tags) OR semantic title similarity
- [ ] Step 4: Classify: NEW | OVERLAPS seed:{slug} | OVERLAPS draft:{slug} | OVERLAPS published:{slug}
- [ ] Step 5: If OVERLAPS published, generate reinforcement_angle (1 line)
- [ ] Step 6: Annotate candidate with dedup_status, overlap_slug, reinforcement_angle

Classification rules

NEW: tag overlap <2 AND title similarity <0.4.
OVERLAPS seed:{slug}: writer has a seed on this; mention is context but NOT a new seed candidate.
OVERLAPS draft:{slug}: writer is actively working on this; may absorb external evidence.
OVERLAPS published:{slug}: writer already shipped on this; becomes reinforcement material for future posts.

Reinforcement angle

When OVERLAPS published: generate a one-line angle the writer could use in a future post.

Example:

Candidate: Transformer Circuits — "Attention as Soft Nearest-Neighbor Lookup"
Overlaps: published attention-as-kernel-regression
Reinforcement angle: "Anthropic's interp team came at this from circuits; I came at it from kernel regression — same answer."

Guardrails

Read-only. Never mutate the ledger. Never propose ledger edits here.
If ledger is stale (>60 days since last touch), emit a warning in digest appendix.
Borderline matches → prefer NEW; false negatives (a missed overlap) are worse UX than false positives (a buried genuine thread).
Reinforcement angles are drafts — writer refines on use. Keep ≤1 sentence.
Never cross-reference with corpus/dead/ — dead ideas should stay dead for Trend Scout's purposes.

---name: cross-ref-topic-ledgerdescription: For each Trend Scout candidate item, checks substacker shared-context/topic-ledger.md and tags with NEW | OVERLAPS seed:{slug} | OVERLAPS draft:{slug} | OVERLAPS published:{slug}. Adds a reinforcement_angle note for items overlapping with published posts ("external confirmation of X"). Read-only against the ledger. Use after summarize-signal, before rank-by-user-fit. Trigger keywords — cross-ref, ledger check, overlap, reinforcement, dedup external.--- # Cross-Ref Topic Ledger ## Workflow ``` Per candidate: - [ ] Step 1: Parse topic-ledger.md into {slug, title, status, tags, last_touched} records - [ ] Step 2: Extract 2-5 topic tags from the candidate's summary (reuse ledger vocabulary) - [ ] Step 3: Match candidate to ledger entries by tag overlap (≥2 shared tags) OR semantic title similarity - [ ] Step 4: Classify: NEW | OVERLAPS seed:{slug} | OVERLAPS draft:{slug} | OVERLAPS published:{slug} - [ ] Step 5: If OVERLAPS published, generate reinforcement_angle (1 line) - [ ] Step 6: Annotate candidate with dedup_status, overlap_slug, reinforcement_angle ``` ## Classification rules - **NEW**: tag overlap <2 AND title similarity <0.4. - **OVERLAPS seed:{slug}**: writer has a seed on this; mention is context but NOT a new seed candidate. - **OVERLAPS draft:{slug}**: writer is actively working on this; may absorb external evidence. - **OVERLAPS published:{slug}**: writer already shipped on this; becomes reinforcement material for future posts. ### Reinforcement angle When OVERLAPS published: generate a one-line angle the writer could use in a future post. Example: - Candidate: Transformer Circuits — "Attention as Soft Nearest-Neighbor Lookup" - Overlaps: published `attention-as-kernel-regression` - Reinforcement angle: "Anthropic's interp team came at this from circuits; I came at it from kernel regression — same answer." ## Guardrails 1. **Read-only.** Never mutate the ledger. Never propose ledger edits here. 2. If ledger is stale (>60 days since last touch), emit a warning in digest appendix. 3. Borderline matches → prefer `NEW`; false negatives (a missed overlap) are worse UX than false positives (a buried genuine thread). 4. Reinforcement angles are drafts — writer refines on use. Keep ≤1 sentence. 5. Never cross-reference with `corpus/dead/` — dead ideas should stay dead for Trend Scout's purposes.

Frequently asked questions