Agent skill

Ref Bridge

by Abilityai in Abilityai/cornelius

Bridge reference entities to the cognitive knowledge base — "this client maps to that insight you had." A thin mode over connection-finder that mounts core,Company/<sub and surfaces entity↔insight…

MITAuto-check: notesKnowledge Management

Install Ref Bridge

skills CLI
$ npx skills add Abilityai/cornelius --skill ref-bridge -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Abilityai/cornelius ref-bridge --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Abilityai/cornelius.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/ref-bridge .claude/skills/ref-bridge && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ref-bridge
GitHub stars
109
Token cost
~2.2k tokens
SKILL.md length
895 words
Files
1
Skills in repo
56
Repo updated
First seen
Licence
MIT

At a glance

Bridge reference entities to the cognitive knowledge base — "this client maps to that insight you had." A thin mode over connection-finder that mounts core,Company/<sub and surfaces entity↔insight…

  • Works in 3 steps: Pick the anchor + read its themes → Theme-seeded CORE search (run BOTH… → Frame the bridges (entity → insight)
  • Tasks that involve Knowledge bases
  • SKILL.md covers Composes, State Dependencies, Process and Verification, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ref Bridge is an agent skill from Abilityai/cornelius. Bridge reference entities to the cognitive knowledge base — "this client maps to that insight you had." A thin mode over connection-finder that mounts core,Company/<sub and surfaces entity↔insight bridges, making the reference scope more than a CRM. READ-ONLY sense — it surfaces candidate bridges for human consideration and MUST refuse to promote a record into an endorsed insight (the guarded encountered→endorsed boundary). Company is the default scope.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Knowledge Management, covering Knowledge bases. The repository describes itself as: AI-powered second brain template for Claude Code + Obsidian. The licence is MIT.

When your agent uses it

  • Tasks that involve Knowledge bases

Example prompts

  • “this client maps to that insight you had.”
  • “/ref-bridge”

Requirements

  • Pre-approved tools (allowed-tools): Read, Bash, Glob, Grep, Skill

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Pick the anchor + read its themes
  2. Theme-seeded CORE search (run BOTH modes; judge relevance)
  3. Frame the bridges (entity → insight)

What it can do on your machine

Read from SKILL.md and the folder at commit fd5e9a4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Bash
    • Glob
    • Grep
    • Skill

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ref Bridge loads about 2.2k tokens when it runs. Until then it costs about 117 tokens; SKILL.md has 895 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Bash, Glob, Grep, Skill

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Abilityai/cornelius at commit fd5e9a4, republished under its MIT licence (© Abilityai). 895 words, ~2,216 tokens.

Download SKILL.mdSave it as .claude/skills/ref-bridge/SKILL.md (or your agent's skills folder).
name
ref-bridge
description
Bridge reference entities to the cognitive knowledge base — "this client maps to that insight you had." A thin mode over connection-finder that mounts core,Company/<sub> and surfaces entity↔insight bridges, making the reference scope more than a CRM. READ-ONLY sense — it surfaces candidate bridges for human consideration and MUST refuse to promote a record into an endorsed insight (the guarded encountered→endorsed boundary). Company is the default scope.
allowed-tools
Read, Bash, Glob, Grep, Skill
automation
manual
user-invocable
true
argument-hint
[scope=Company] <entity name or sub-scope, e.g. 'Acme Corp' | 'engagements'>
metadata.version
1.1
metadata.created
2026-07-08
metadata.author
Cornelius
metadata.changelog
1.2: Fix — spreading mode drifts to the KB's densest hub (Identity/Dopamine), returning spurious bridges for cross-cluster entities (most Company…

Ref Bridge

ℹ️ First, set expectations: before anything else, print one short line with this skill's version and its most recent change — the top entry of metadata.changelog above — e.g. ref-bridge v1.0 — recent: initial version. Then proceed.

Why reference data lives in the brain and not in a spreadsheet. A CRM stores clients; a second brain can tell you which of your insights a client is a live instance of. ref-bridge mounts a reference sub-scope alongside core and finds the bridges from an entity to the user's cognitive notes ("Acme Corp, the lighthouse deal ↔ your note on land-and-expand / reference-customer leverage").

It is read-only sense. It surfaces candidates; it never writes, and — critically — it never promotes a record into an endorsed insight. A record informing a thought is fine; a record becoming the user's originated/endorsed thought is the one line the reference kind exists to hold, and it stays the human encountered → endorsed act.

Read first: resources/layered-brains/COMPANY-BRAIN-SCHEMA.md → "The playbook suite" (ref-bridge row) + "Automation boundary"; resources/layered-brains/REFERENCE-SCOPE-SCHEMA.md.

Composes

  • /find-connections — the connection-discovery engine; this skill runs it with the reference scope mounted and frames the output as entity→cognitive-note bridges. (Do not re-implement connection logic.)

State Dependencies

SourceLocationReadWriteDescription
Company familyBrain/Company/*/*.md✓The entity anchor(s)
Core KB + wrappersBrain/{02-Permanent,03-MOCs,AI Extracted Notes,01-Sources}/, resources/local-brain-search/run_connections.sh · run_search.sh✓Bridged-to cognitive notes

Process

Step 1 — Pick the anchor + read its themes

Resolve the entity note (or take a whole sub-scope) and read it to extract its distinctive themes — the economic/strategic concepts it embodies, not its proper nouns (e.g. Acme Corp's engagement = "one lighthouse deal deposits a reusable blueprint + license ARR + a reference case" → themes: optionality / one-bet-many-payoffs, reusable-asset leverage, reference-proof credibility). These themes are the query surface — the bridge is to the insight a fact instantiates, so search by concept.

Step 2 — Theme-seeded CORE search (run BOTH modes; judge relevance)

A reference note's own precomputed edges cluster tightly with its siblings (all engagement notes look alike), and mounting core,Company/<sub> lets those siblings crowd out core in the results. So the method that actually surfaces entity→insight bridges is a theme-seeded search of core alone, using KB-aligned vocabulary — run in both modes, because they fail differently:

bash
# the bridge: which of the user's insights is this entity a live instance of?
BRAIN_READ_SCOPE=core resources/local-brain-search/run_search.sh "<entity themes, KB vocabulary>" --mode static    --threshold 0.35 --limit 6 --json
BRAIN_READ_SCOPE=core resources/local-brain-search/run_search.sh "<entity themes, KB vocabulary>" --mode spreading --threshold 0.35 --limit 6 --json

static is the primary finder for cross-cluster bridges; spreading drifts to the KB's densest hub. Spreading activation flows toward high-centrality nodes — in this KB the Identity / Dopamine / Eight-Circuit cluster. For an entity whose true theme lives outside that cluster (agent architecture, orchestration, GTM — i.e. most Company products, agents, and engagements), spreading returns plausible-but-spurious Identity/Dopamine bridges while static returns the right ones (validated 2026-07-08: Trinity Cloud, themed "agent orchestration / harness is the constraint / architecture over models" → "Most AI agents are chatbots with fancy wrappers" · MOC - AI and Agents under static; → Identity/Dopamine notes under spreading). Only when the entity's theme is the dense decision-science/consciousness core do the two agree (Acme Corp's decision-science theme → Decision Making · Prospect Theory · Loss Aversion under both). Read the candidates and judge whether each insight actually relates to the entity's theme — never take top-k on trust.

Threshold is a floor, not a filter to game. Reference entity bodies are terse; --threshold 0.35 is a safe floor that keeps genuinely-related notes a higher cut would drop. Depending on the query, a 0.5 cut may return the same bridges or an empty set (seed_count: 0) — it is query-dependent, not a universal failure. So if a theme returns nothing, re-phrase toward the KB's actual concepts rather than assuming the threshold is the problem.

Show full SKILL.md (329 more words)Show less

Query core vocabulary, not book-shelf vocabulary. Concepts like antifragility / optionality / convexity live in the non-core Books/ shelf, so they return nothing under a core mount — phrase the theme in the core KB's own words (decision science, uncertainty, prospect theory, asymmetric payoff, ergodicity). If you genuinely want to bridge to book-shelf concepts, add Books to the mount (BRAIN_READ_SCOPE=core,Books).

Optionally also mount the sub-scope (core,Company/<sub>) and run /find-connections on the entity to make it co-visible in a graph view — but treat the theme-seeded core search as the primary finder. The mounted read is non-pure-core, so it trains no q-values (learn-gate holds; verify data/q_values.json byte-unchanged as the positive control). If a theme returns nothing above threshold, re-phrase toward the KB's actual concepts rather than lowering rigor.

Step 3 — Frame the bridges (entity → insight)

Present each bridge as: entity fact → the cognitive note it instantiates → why. Prefer bridges to 02-Permanent / AI Extracted Notes (the user's own thinking) over other reference notes. Label everything as AI-surfaced candidates for human consideration — not endorsed links.

markdown
## Bridges for [[Acme Corp - Trinity Enterprise Build]]
- ↔ [[<permanent note>]] — this lighthouse deal is a live instance of <the insight>. (candidate)
- ↔ [[<permanent note>]] — the $20K license ARR echoes <the pricing/optionality note>. (candidate)

Verification

  • A theme-seeded core search (at --threshold 0.35) on a real entity's concepts surfaces at least one bridge to a core cognitive note, framed as entity→insight with a reason. For a cross-cluster entity, --mode static surfaces the on-theme bridges that --mode spreading misses by drifting to the Identity/Dopamine hub — both modes are run and the on-theme one is kept (verified 2026-07-08: Trinity Cloud → MOC - AI and Agents under static, Identity/Dopamine under spreading). For a core-cluster entity both agree (Acme Corp → Decision Making · Prospect Theory · Loss Aversion).
  • With core,Company/<sub> mounted, the reference entity is co-visible; unset, it is absent from all readers (reference stays invisible by default) — the isolation control.
  • Nothing is written; data/q_values.json is byte-unchanged after the pass.

This skill must refuse to

  • Write or mutate any note (read-only sense).
  • Promote a reference record into an endorsed/originated cognitive insight, or create a permanent note from a record — that is the human encountered → endorsed act.
  • Crystallize, lifecycle-classify, or synthesis-pulse a reference note.

© Abilityai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/ref-bridge of Abilityai/cornelius.

Open the folder on GitHubat commit fd5e9a4

Compare with similar skills

Ref Bridge next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ref Bridge compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ref Bridge this skillAbilityai/cornelius109—~2.2kAutomated safety check: NotesMIT
Customer Researchw95/awesome-claude-corporate-skills235—~2.3kAutomated safety check: PassMIT
Knowledge Base Designrevfactory/harness-1001.3k—~897Automated safety check: PassApache-2.0
LLM Wiki Knowledge GraphEgonex-AI/Understand-Anything85k1 repos~1.5kAutomated safety check: PassMIT
Xhs Virtual Productchenjin-cmd/xhs-virtual-product726—~862Automated safety check: PassMIT
OpenkbVectifyAI/OpenKB4.7k1 repos~2kAutomated safety check: WarnApache-2.0

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Questions about Ref Bridge

What does Ref Bridge do?

Bridge reference entities to the cognitive knowledge base — "this client maps to that insight you had." A thin mode over connection-finder that mounts core,Company/<sub and surfaces entity↔insight…. Ref Bridge is an agent skill from Abilityai/cornelius." A thin mode over connection-finder that mounts core,Company/<sub and surfaces entity↔insight bridges, making the reference scope more than a CRM.

When should I use Ref Bridge?

Ref Bridge fits situations like: tasks that involve Knowledge bases.

How do I install Ref Bridge in Claude Code?

Run `npx skills add Abilityai/cornelius --skill ref-bridge -a claude-code`. Or copy the skill folder (.claude/skills/ref-bridge in Abilityai/cornelius) into .claude/skills/ref-bridge in your project. Claude Code loads it when a task matches its description.

How do I install Ref Bridge in Codex?

Run `npx skills add Abilityai/cornelius --skill ref-bridge -a codex`. Or copy the skill folder (.claude/skills/ref-bridge in Abilityai/cornelius) into .agents/skills/ref-bridge in your project. Codex loads it when a task matches its description.

Can I use Ref Bridge in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Abilityai/cornelius --skill ref-bridge -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ref-bridge, .gemini/skills/ref-bridge, .github/skills/ref-bridge and .opencode/skills/ref-bridge in your project.

What does Ref Bridge need to run?

SKILL.md names no scripts, command-line tools or credentials: Ref Bridge is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Bash, Glob, Grep, Skill.

Does Ref Bridge access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ref Bridge safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Ref Bridge use?

Ref Bridge is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ref Bridge use?

About 2.2k tokens (SKILL.md is roughly 8.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ref Bridge?

Skills that share tags, products or a category with Ref Bridge: Customer Research (w95/awesome-claude-corporate-skills, 235 stars), Knowledge Base Design (revfactory/harness-100, 1.3k stars), LLM Wiki Knowledge Graph (Egonex-AI/Understand-Anything, 85k stars) and Xhs Virtual Product (chenjin-cmd/xhs-virtual-product, 726 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ref Bridge?

Abilityai (a GitHub organization) maintains it in Abilityai/cornelius, which has 109 GitHub stars. The repository holds 56 skills in this directory. The repository was last updated on September 22, 2026.

Source: Abilityai/cornelius on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.