j-space
Skill8 starsChanged 2 months agoMITView on GitHub
Operate the agent's inner cognitive workspace for multi-step reasoning, long-horizon planning, deep debugging, and calibrated self-monitoring. Use when tackling complex multi-step problems, architecture design, long mechanical tasks requiring goal preservation, suspicious input audits, or when asked to think deeper or harder — even if they don't explicitly say \"J-space\". Do NOT use for single-step trivial lookups, basic formatting, or conversational small talk.
We split this skill into the rules it gives an agent
6 rules. 0 are common, 5 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 8 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
Restate Requirement Before Solving: Before answering any non-trivial prompt, restate the requirement in one line in your own words to …
- Distinctive: line 28
No Blind Completion: Never mark a task finished without re-reading the initial goal line-by-line and verifying all acceptance criteria.
- Very specific: line 68
Key Point: If you cannot verify the answer in a single glance, it is never fast.
- Distinctive: line 73
Key Point: Keep the ledger updated at every seam: Goal, Settled items, Open questions, Next single action.
- Distinctive: line 82
Key Point: If an approach fails, declare a marker, perform the bound corrective action, and settle before continuing.
- Distinctive: line 87
Key Point: No private symbols or unstructured fragments in user-facing deliverables.
“Common” is measured: kept by at least 6 in 10 of the 8 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
J-Space: Inner Cognitive Workspace
Operate the model's inner cognitive workspace (J-space) for multi-step chained reasoning, long-horizon planning, complex debugging, calibrated confidence, global consistency, and resistant self-monitoring.
The J-Space Premise
You do not only produce words; you also reason before — and without — immediately emitting them. J-space holds what you are poised to say: concepts you can hold in mind deliberately, reason with silently, and broadcast to downstream computations.
Core Invariants
- Restate Requirement Before Solving: Before answering any non-trivial prompt, restate the requirement in one line in your own words to anchor the reasoning chain.
- Three Explicit Registers:
- Inner: Dense, private, chained reasoning track.
- Ledger: Durable state tracking (Goal, Settled, Open, Next). Checked at every seam.
- Outer: Clean, complete, professional communication delivered to the user.
- The Gating Floor: Classify the task before loading heavy machinery:
fast: Single-step direct answers verifiable in one glance.full: 2–4 steps, single deliverable, verifiable in one reading.loop: Multi-stage, multi-file, multi-turn stateful work.
- Seam Audits: At every seam (sub-task completion, file write, tool call, deliverable checkpoint), audit the ledger before proceeding.
- No Blind Completion: Never mark a task finished without re-reading the initial goal line-by-line and verifying all acceptance criteria.
Architecture & Map of Content (MOC)
[ Incoming Task ] ──► [ Restate Requirement ] ──► [ Task Gate: Fast / Full / Loop ]
│
▼
┌──────────────────────────────────────────────────────────┐
│ J-Space Cognitive Loop │
│ ├─ Inner Register (Chained intermediate reasoning) │
│ ├─ Ledger Register (Goal / Open / Settled / Next) │
│ └─ Seam Audit (Check invariants at each transition) │
└───────────────────────────┬──────────────────────────────┘
│
▼
[ Outer Register Delivery ]| Functional Property | Cognitive Purpose | Failure Mode Prevented |
| Capacity Selectivity | Only 1–2 active concepts on stage at once | Attention thinning & overloaded context |
| Directed Focus | Goal remains active through tedious middle | Goal evaporation during mechanical tasks |
| Deep Reasoning | Intermediate bridges form before conclusions | Rationalizing unverified gut guesses |
| Self-Monitoring | Calibrated confidence & error detection | Overconfident halluncinations |
| Seam Auditing | State refreshed at every transition | Context drift over long execution turns |
Step-by-Step Procedure (TWI)
Step 1: Awakening & Requirement Re-Encoding
- Action: Restate the requirement in one line, in your own words, before writing code or making tool calls.
- Key Point: Re-encoding buys back recurrence and anchors the goal representation.
- Why: Skipping re-encoding leads to shallow interpretation of multi-constraint prompts.
Step 2: Task Gate Classification
- Action: Classify into
fast,full, orlooppass. - Key Point: If you cannot verify the answer in a single glance, it is never
fast. Escalating costs nothing. - Why: Under-classifying complex tasks causes premature shortcutting.
Step 3: Operate the Three Registers
- Action: Think in the inner register, record state in the ledger, and speak in the outer register.
- Key Point: Keep the ledger updated at every seam: Goal, Settled items, Open questions, Next single action.
- Inline Checklist:
- Requirement re-encoded
- Correct pass classified
- Ledger reflects current state
- Verification criteria stated explicitly
Step 4: Seam Refresh & Invariant Verification
- Action: At every seam (file written, subagent returned, tool executed), check that invariants hold.
- Key Point: If an approach fails, declare a marker, perform the bound corrective action, and settle before continuing.
- Why: Continuing down a broken path wastes turns and produces compounding errors.
Step 5: Clean Outer Delivery
- Action: Translate settled conclusions into clean outer-register deliverables.
- Key Point: No private symbols or unstructured fragments in user-facing deliverables.
- Why: Deliverables must be immediately usable, clear, and actionable.
Anti-Rationalization Guardrails
| Tempting Rationalization | Binding Rule | Engineering Rationale |
| "This is simple enough, skip the ledger." | Enforce the floor: multi-step work requires ledger tracking. | Unsettled state drops out of context during long turns. |
| "The first guess sounds right, skip the intermediate step." | Derive intermediate bridges before adopting conclusions. | Pretrained fluency often produces plausible but flawed shortcuts. |
| "I will clean up the verification at the very end." | Verify at every seam, not just at the end. | Errors caught early require small fixes; late discoveries require total rewrites. |
| "Confidence is always high across all steps." | Calibrate confidence per step. | Uniform confidence indicates disabled self-monitoring. |
Other versions8 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 8
- Tiger3807861189/J-Space-Cognition-Suite★ 3ksame name
- Tiger3807861189/J-Space-Cognition-Suite-V3.7★ 3ksame name
- DJG3DK/3D-Agent★ 3same name
- DJG3DK/persei★ 3same name
- DJG3DK/tektonix★ 3same name
- carterlasalle/skills★ 1same name
- yjhqwer/yjh-discipline★ 1same name
- puntorigen/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.
Used alongsideProjects with it also use webapp-testing.
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.
JetBrainsSkillwebapp-testing
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Also in 3 projects that use this
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- teachSkill
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- wait-whatSkill
- wayfinderSkill
- wizardSkill
- workflow-designerSkill
- writing-beatsSkill
- writing-for-agentsSkill
- writing-fragmentsSkill
- writing-shapeSkill
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