Cognitive Lensing Framework

VerifiedSafe

Apply multilingual cognitive frames to re-approach complex tasks with targeted reasoning patterns and bias checks. Unlock alternative solution paths through disciplinary perspectives and structured heuristics.

Sby Skills Guide Bot
ProductivityIntermediate
3/11/2026
Claude Code
#reasoning#cognitive-frames#bias-checking#decision-making#problem-solving

Recommended for

Automated summary

Applies switchable cognitive frames (linguistic, disciplinary, or persona lenses) to re-approach a complex task from several angles and surface reasoning biases.

Strengths

  • Requires naming the lens, heuristic, and expected impact on each pass, keeping the reasoning traceable.
  • Deliberately caps each pass at 2-3 lenses and demands explicit confidence ceilings to prevent speculative overclaiming.
  • Ships concrete trigger conditions (analytical stagnation, unclear user impact, risky changes) plus a list of anti-patterns to avoid.
  • Includes a synthesis phase that compares lens insights and outputs prioritized next steps.

Limitations

  • Produces no technical artifact: the output is analysis and next actions to be executed elsewhere.
  • Value depends entirely on lens selection, which is left to the model's judgment.
  • Relies on Claude Code-specific tools (Task, TodoWrite) and an optional memory MCP to be fully effective.
When to use it

Use it when reasoning is stuck or when a blind spot (security, accessibility, user impact) needs to be probed before a significant decision.

When not to use it

Avoid it for a plain prompt rewrite or for building an agent, which are handled by the dedicated upstream and downstream skills.

Security analysis

Safe
Quality score75/100

The skill is a pure reasoning/reframing procedure. It contains no shell commands, no network calls, no credential handling, no file mutation instructions, and no attempts to disable safety behavior. The declared tool list is broader than needed (Bash/Write/Edit are unused by any phase), which is a least-privilege nit rather than a threat. All guidance stays at the level of naming lenses, citing evidence, and stating confidence ceilings.

Findings
  • •Declares privileged tools (Write, Edit, Bash) that the SOP never actually requires — capability is broader than the task, though no instruction invokes them.
How this analysis is made

Examples

Unblock an architecture decision
I keep going back and forth between a managed queue and a self-hosted broker. Apply two opposing lenses (reliability/ops vs. cost and complexity), then give me a synthesis with explicit confidence levels.
Pre-deployment API review
Before we ship the new payments API, run a security red-team lens and a reliability lens on the rollout plan, list the failure paths, and rank the priority actions.
Rewrite a setup guide
Our installation guide is unreadable. Run it through an accessibility lens and an onboarding UX lens, then propose concrete rewrites.

name: cognitive-lensing description: Apply multilingual cognitive frames to re-approach complex tasks with targeted reasoning patterns and bias checks. allowed-tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite model: sonnet x-version: 3.2.0 x-category: foundry x-vcl-compliance: v3.1.1 x-cognitive-frames:

  • HON
  • MOR
  • COM
  • CLS
  • EVD
  • ASP
  • SPC

L1 Improvement

  • Recast the lensing guide into the Skill Forge section flow with explicit guardrails, patterns, and completion checks.
  • Added prompt-architect style constraint extraction and confidence ceilings to prevent overclaiming from speculative frames.

STANDARD OPERATING PROCEDURE

Purpose

Switch reasoning frames (linguistic, disciplinary, or persona-based) to unlock alternative solution paths and mitigate bias in complex tasks.

Trigger Conditions

  • Positive: stalled reasoning, need for alternative perspectives, bias detection, or creative exploration.
  • Negative/reroute: straightforward prompt rewrites (prompt-architect) or agent creation (agent-creator/agent-creation).

Guardrails

  • Keep outputs in English; cite which lens was applied and why.
  • Do not fabricate expertise—ground lens choice in task constraints and evidence.
  • Limit to 2-3 focused lenses per pass to avoid fragmentation.
  • State confidence ceilings explicitly, especially when using speculative or research lenses.

Execution Phases

  1. Assessment: Capture task intent, constraints, and observed failure modes; classify hard/soft/inferred constraints.
  2. Lens Selection: Choose lenses (e.g., formal proof, UX research, security red-team, socio-technical) mapped to the task.
  3. Application: Re-articulate the problem through each lens with targeted heuristics and checks.
  4. Synthesis: Compare insights, resolve conflicts, and propose next actions with confidence ceilings.

Pattern Recognition

  • Analytical stagnation → apply formal/algorithmic lens.
  • User impact unclear → apply UX research or accessibility lens.
  • Risky changes → apply safety/security lens to uncover failure paths.

Advanced Techniques

  • Use paired lenses (builder vs breaker) to surface hidden assumptions.
  • Run time-boxed divergent thinking followed by convergence synthesis.
  • Feed lens outputs into prompt-architect for clarity before execution.

Common Anti-Patterns

  • Cycling too many lenses without decision.
  • Treating lens opinions as facts; neglecting evidence and ceilings.
  • Ignoring domain constraints when adopting a lens.

Practical Guidelines

  • Name the lens, heuristic, and expected impact in each pass.
  • Keep synthesized recommendations actionable and prioritized.
  • Capture what changed between lenses for traceability.

Cross-Skill Coordination

  • Upstream: prompt-architect to clarify the task.
  • Parallel: recursive-improvement to iterate on stuck areas; meta-tools to compose lens outputs into tools.
  • Downstream: agent-creation/agent-selector to operationalize chosen approach.

MCP Requirements

  • Optional memory MCP to recall past lens effectiveness; tag WHO=cognitive-lensing-{session}, WHY=skill-execution.

Input/Output Contracts

inputs:
  task: string  # required problem statement
  constraints: list[string]  # optional constraints
  target_lenses: list[string]  # optional lens hints (e.g., security, accessibility)
outputs:
  lens_analyses: list[object]  # lens name, insight, risks
  synthesis: summary  # consolidated recommendation
  next_steps: list[string]  # actions derived from lensing

Recursive Improvement

  • Run recursive-improvement when lenses disagree or output is indecisive; focus on evidence gaps and decision criteria.

Examples

  • Apply security red-team + reliability lens to a new API rollout before deployment.
  • Use accessibility + onboarding UX lens to rewrite a complex setup guide.

Troubleshooting

  • Lens produces no new insight → select orthogonal lens or consult domain specialists.
  • Conflicting recommendations → prioritize by risk, effort, and evidence strength.
  • Overconfident claims → restate with ceilings and cite observed data.

Completion Verification

  • [ ] Lenses named with rationale and heuristics applied.
  • [ ] Synthesis provided with prioritized actions and ceilings.
  • [ ] Traceability of changes between lenses captured.
  • [ ] Constraints respected; English-only output.

Confidence: 0.70 (ceiling: inference 0.70) - Lensing SOP rewritten with Skill Forge cadence and prompt-architect ceilings.

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/cognitive-lensing-framework-mmlj2nya/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/cognitive-lensing-framework-mmlj2nya' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/cognitive-lensing-framework-mmlj2nya/download' --output '.skill-downloads/cognitive-lensing-framework-mmlj2nya/SKILL.md.part' && mv '.skill-downloads/cognitive-lensing-framework-mmlj2nya/SKILL.md.part' '.skill-downloads/cognitive-lensing-framework-mmlj2nya/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Tools declared by the author (check availability in your agent): Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/cognitive-lensing-framework-mmlj2nya/SKILL.md' && test -s '.skill-downloads/cognitive-lensing-framework-mmlj2nya/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/cognitive-lensing' && cp -R '.skill-downloads/cognitive-lensing-framework-mmlj2nya' '.claude/skills/cognitive-lensing'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/cognitive-lensing-framework-mmlj2nya'

openskills read 'cognitive-lensing-framework-mmlj2nya'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/cognitive-lensing-framework-mmlj2nya/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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