deepen
Skill0 starsChanged 48 days agoMITView on GitHub
Escalate a captured source record to a deeper reading pass — fill in evidence quality, extract addressable claims, connect it to the vault with typed relations. Use when the user says /deepen {note}, "process this source", "go deeper on this capture", or wants a captured source properly read.
10 other projects use a version of this.
Adopted by
Most recently taken up by
- hideki5123/agent-skill-settheir own version, first seen Nov 1, 2026
- mehrad-dm/mastermindtheir own version, first seen Oct 13, 2026
- nino-chavez/agentic-ways-of-workingtheir own version, first seen Oct 13, 2026
- krixon/skillstheir own version, first seen Oct 11, 2026
- mattbutlerengineering/skillstheir own version, first seen Oct 11, 2026
- SubliminalCoding/bilbroswagginz-skillstheir own version, first seen Sep 27, 2026
Used with
Projects with it also use zoom-out, diagnose and 2 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
victorgarciaesgiSkillzoom-out
Tell the agent to zoom out and give broader context or a higher-level perspective. Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.
Also in 3 projects that use this
MicrosoftSkilldiagnose
Use to systematically diagnose why scenarios fail — identifies root causes by analyzing agent traces, codebase, and behavioral patterns
Also in 3 projects that use this
GoogleSkilltdd
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
Also in 3 projects that use this
MicrosoftSkillhandoff
Compact the current conversation into a handoff document for another agent to pick up.
Also in 3 projects that use this
Other versions10 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 10
- JuliusBrussee/cavekit★ 1.1ksame name
- mehrad-dm/mastermind★ 23same name
- Brianhkerr/deepen-skill★ 3same name
- hideki5123/agent-skill-set★ 2same name
- nino-chavez/agentic-ways-of-working★ 2same name
- bdunn313/repolab★ 1same name
- krixon/skills★ 1same name
- mattbutlerengineering/skills★ 1same name
- qmertesdorf/GameForge★ 0same name
- SubliminalCoding/bilbroswagginz-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository10 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- classifySkill
- consultSkill
- defuddleSkill
- knowSkill
- librarianSkill
- reviewSkill
- synthesizeSkill
- vault-installSkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 2 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 7 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
This builds retrieval, not understanding: After deepening, offer the user one retrieval question drawn from the extracted claims ("From …
- Very specific: line 39
Search the vault for related material: existing area notes (40-areas/), concepts (50-resources/concepts/), and other source records' claims.
- Very specific: line 54
If 00-meta/questions.md exists and a claim answers an open question, add the ID to answers: [] and note it in your report.
- Very specific: line 58
Only on explicit request. Append a ## Reconstruction section:
- Distinctive: line 69
If the source turned out shallower than its capture suggested, say so — downgrading expectations is a valid outcome.
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
/deepen — escalate a source record's reading depth
Take one source record (from 50-resources/sources/) one level up the processing ladder:
captured → processed → connected (a third, reconstruction-grade pass stays connected; synthesized is set only when an area note actually incorporates the source — that's synthesis work, not deepening).
Resolve the argument to a note path (search 50-resources/sources/ by slug/title/URL if given loosely). If it's a bookmark, offer to promote it first: create the source record per /know's schema, add promoted_to: "[[<source record>]]" to the bookmark, then deepen the record.
Contract (binding)
- Never rewrite existing prose. Fill empty sections and append; if a filled section needs revision, propose it to the user instead of editing. The human's words outrank yours.
- Own words only. Quotes belong in the evidence package, cited from the record.
- This builds retrieval, not understanding. After deepening, offer the user one retrieval question drawn from the extracted claims ("From memory: what does X claim about Y?"). Optional, never blocking.
- One note per invocation. Deepening is expensive by design; batching it recreates shallow capture.
Pass 2 — captured → processed
Actually read the source (fetch fully; for a repo, read README + key entry points; for a paper, the full text if reachable — retain it as an evidence package if you had to fetch something ephemeral).
Video sources: read the full transcript in the evidence package and view the retained frames — slides often carry claims the speech only gestures at; extract slide content (numbers, architecture, tables) into claims. When the transcript references a visual moment that has no retained frame ("as you can see here…", "this slide shows…"), re-fetch the video to the scratchpad (yt-dlp -f "bv*[height<=1440]/bv*"), grab the exact frame (ffmpeg -ss <m:ss> -i <video> -frames:v 1 -q:v 2), view it, and add it to frames/<mm-ss>-<hint>.png if it earns its place. Delete the video afterward. Claims from a video cite their timestamp: … (12:34).
Fill these body sections (create any that are missing, in this order):
## Source and evidence quality— who made this, with what incentive; is it experience report, opinion, benchmark, peer-reviewed; how would a claim here be checked.## Claims and evidence— one bullet per claim, own words, each ending with^claim-<idea-slug>(idea-named, unique in file, never renamed once written). 3–8 claims; fewer honest claims beat exhaustive paraphrase. Note per claim what evidence backs it (assertion / example / data / proof).## Limitations or counterarguments— where it's thin, what it ignores, who would disagree.
Gate before advancing state. Before setting processing: processed, check every bullet in ## Claims and evidence for a trailing ^claim-<slug> anchor. A claim bullet without one isn't addressable — /synthesize can't cite it at block granularity, and /review's promotion count can't see it — so it isn't a completed pass 2 regardless of how much prose surrounds it. Add the missing anchors before advancing state; don't advance state and leave them for later (a 2026-08-16 audit found 30 of 33 processed+ records in this vault missing anchors entirely, all bulk-migrated before this gate existed — don't grow that number further).
Then set processing: processed, bump updated.
Connect pass — processed → connected
Search the vault for related material: existing area notes (40-areas/), concepts (50-resources/concepts/), and other source records' claims. Fill:
## Connections— typed inline fields only, from the closed vocabulary:supports:: [[Note or Note#^claim-slug]] — optional qualifier extends:: [[...]] contradicts:: [[...]] — on <what, specifically> special-case-of:: [[...]] supersedes:: [[...]]Write relations on this note pointing at the older/more canonical note; don't hand-maintain inverses. Prefer claim-block targets when the relation is about one claim. A few labeled edges beat many bare links — if you can't type it, it isn't a connection worth recording.
## Synthesis usage— leave empty unless an area note already cites this source; then link it.
If 00-meta/questions.md exists and a claim answers an open question, add the ID to answers: [] and note it in your report. Then set processing: connected, bump updated.
Pass 3 — reconstruction (stays connected)
Only on explicit request. Append a ## Reconstruction section:
- Repo/system: how it actually works (data flow, key mechanisms) and how you would have built it — where your design would differ and why.
- Paper: work the argument — restate the method, check whether the conclusions follow, identify the load-bearing assumption.
This pass often produces new claims (add them to ## Claims and evidence with block IDs) and new open questions (add to 00-meta/questions.md if it exists; otherwise list them in the section).
Report
- Append one row to
00-meta/log.md:| YYYY-MM-DD | ingest | /deepen: <title> → <new processing state>, <n> claims extracted |. - Summarize: new state, claims extracted (with slugs), relations added, questions touched.
- If the source turned out shallower than its capture suggested, say so — downgrading expectations is a valid outcome.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

