Skill: aipoch-ai/market-access-value (version 1.0.0)

--- name: market-access-value description: Use market access value for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries. license: MIT skill-author: AIPOCH --- # Market Access Value Payer value proposition development. ## When to Use - Use this skill when the task needs Use market access value for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries. - Use this skill for academic writing tasks that require explicit assumptions, bounded scope, and a reproducible output format. - Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence. ## Key Features - Scope-focused workflow aligned to: Use market access value for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries. - Packaged executable path(s): `scripts/main.py`. - Reference material available in `references/` for task-specific guidance. - Structured execution path designed to keep outputs consistent and reviewable. ## Dependencies See `## Prerequisites` above for related details. - `Python`: `3.10+`. Repository baseline for current packaged skills. - `Third-party packages`: `not explicitly version-pinned in this skill package`. Add pinned versions if this skill needs stricter environment control. ## Example Usage ```bash cd "20260318/scientific-skills/Academic Writing/market-access-value" python -m py_compile scripts/main.py python scripts/main.py --help ``` Example run plan: 1. Confirm the user input, output path, and any required config values. 2. Edit the in-file `CONFIG` block or documented parameters if the script uses fixed settings. 3. Run `python scripts/main.py` with the validated inputs. 4. Review the generated output and return the final artifact with any assumptions called out. ## Implementation Details See `## Workflow` above for related details. - Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable. - Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script. - Primary implementation surface: `scripts/main.py`. - Reference guidance: `references/` contains supporting rules, prompts, or checklists. - Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints. - Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects. ## Quick Check Use this command to verify that the packaged script entry point can be parsed before deeper execution. ```bash python -m py_compile scripts/main.py ``` ## Audit-Ready Commands Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths. ```bash python -m py_compile scripts/main.py python scripts/main.py --help ``` ## Workflow 1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work. 2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions. 3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available. 4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items. 5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion. ## Use Cases - HTA submissions - Payer negotiations - Pricing strategy - Reimbursement applications ## Parameters - `drug_profile`: Efficacy/safety data - `comparator`: Standard of care - `market`: US/EU/Japan pricing ## Returns - ICER calculation narrative - Budget impact model text - Value dossier sections - Payer objection handlers ## Example ICER = $45,000/QALY with uncertainty analysis ## Risk Assessment | Risk Indicator | Assessment | Level | |----------------|------------|-------| | Code Execution | Python/R scripts executed locally | Medium | | Network Access | No external API calls | Low | | File System Access | Read input files, write output files | Medium | | Instruction Tampering | Standard prompt guidelines | Low | | Data Exposure | Output files saved to workspace | Low | ## Security Checklist - [ ] No hardcoded credentials or API keys - [ ] No unauthorized file system access (../) - [ ] Output does not expose sensitive information - [ ] Prompt injection protections in place - [ ] Input file paths validated (no ../ traversal) - [ ] Output directory restricted to workspace - [ ] Script execution in sandboxed environment - [ ] Error messages sanitized (no stack traces exposed) - [ ] Dependencies audited ## Prerequisites No additional Python packages required. ## Evaluation Criteria ### Success Metrics - [ ] Successfully executes main functionality - [ ] Output meets quality standards - [ ] Handles edge cases gracefully - [ ] Performance is acceptable ### Test Cases 1. **Basic Functionality**: Standard input → Expected output 2. **Edge Case**: Invalid input → Graceful error handling 3. **Performance**: Large dataset → Acceptable processing time ## Lifecycle Status - **Current Stage**: Draft - **Next Review Date**: 2026-03-06 - **Known Issues**: None - **Planned Improvements**: - Performance optimization - Additional feature support ## Output Requirements Every final response should make these items explicit when they are relevant: - Objective or requested deliverable - Inputs used and assumptions introduced - Workflow or decision path - Core result, recommendation, or artifact - Constraints, risks, caveats, or validation needs - Unresolved items and next-step checks ## Error Handling - If required inputs are missing, state exactly which fields are missing and request only the minimum additional information. - If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment. - If `scripts/main.py` fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback. - Do not fabricate files, citations, data, search results, or execution outcomes. ## Input Validation This skill accepts requests that match the documented purpose of `market-access-value` and include enough context to complete the workflow safely. Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond: > `market-access-value` only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill. ## References - [references/audit-reference.md](references/audit-reference.md) - Supported scope, audit commands, and fallback boundaries ## Response Template Use the following fixed structure for non-trivial requests: 1. Objective 2. Inputs Received 3. Assumptions 4. Workflow 5. Deliverable 6. Risks and Limits 7. Next Checks If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.

path: market-access-value_audit_result_v2.json
content: {
  "meta": {
    "skill_name": "market-access-value",
    "evaluated_on": "2026-03-23",
    "evaluator_version": "skill-auditor@1.0",
    "category": "Academic Writing",
    "execution_mode": "B",
    "complexity": "Moderate",
    "n_inputs": 5
  },
  "veto_gates": {
    "skill_veto": {
      "stability": "PASS",
      "contract": "PASS",
      "determinism": "PASS",
      "security": "PASS",
      "gate": "PASS"
    },
    "research_veto": {
      "applicable": true,
      "scientific_integrity": {
        "result": "PASS",
        "detail": "Scientific integrity remained intact because the package rewrote or structured material without fabricating findings."
      },
      "practice_boundaries": {
        "result": "PASS",
        "detail": "The archived review kept this package within Use market access value for academic writing workflows that need structured execution,..., not result fabrication or expert advice."
      },
      "methodological_ground": {
        "result": "PASS",
        "detail": "No methodological-grounding issue was recorded for market-access-value in the archived evaluation."
      },
      "code_usability": {
        "result": "N/A",
        "detail": "This package is judged mainly on writing behavior, so code usability is not a central evaluation target here."
      },
      "gate": "PASS"
    }
  },
  "static_score": {
    "subtotal": 88,
    "max": 100,
    "categories": {
      "functional_suitability": {
        "score": 11,
        "max": 12,
        "note": "Functional fit remained strong, though the final communication package could still be a little tighter."
      },
      "reliability": {
        "score": 10,
        "max": 12,
        "note": "Reliability was softened by the legacy issue 'Stabilize executable path and fallback behavior'. Some inputs only reached PARTIAL due to execution gaps or weak boundary handling"
      },
      "performance_context": {
        "score": 8,
        "max": 8,
        "note": "No point loss was recorded for performance context in the legacy audit."
      },
      "agent_usability": {
        "score": 14,
        "max": 16,
        "note": "Agent usability was strong, though the workflow could surface its main conversion branches more directly."
      },
      "human_usability": {
        "score": 8,
        "max": 8,
        "note": "The legacy audit gave full marks to human usability for this package."
      },
      "security": {
        "score": 10,
        "max": 12,
        "note": "The workflow stayed safe overall, with only a small remaining deduction around boundary signaling."
      },
      "maintainability": {
        "score": 10,
        "max": 12,
        "note": "The workflow is low-risk to maintain, though a little more structural cleanup would likely close the remaining gap."
      },
      "agent_specific": {
        "score": 17,
        "max": 20,
        "note": "The archived deduction in agent specific traces back to: Stabilize executable path and fallback behavior. Some inputs only reached PARTIAL due to execution gaps or weak boundary handling"
      }
    }
  },
  "dynamic_score": {
    "execution_avg": 83.6,
    "max": 100,
    "assertion_pass_rate": {
      "passed": 18,
      "total": 20
    },
    "inputs": [
      {
        "index": 1,
        "type": "Canonical",
        "label": "Use market access value for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries",
        "status": "COMPLETED",
        "status_flag": "PASS",
        "note": "The archived evaluation treated Use market access value for academic writing workflows that need... as a clean in-scope run.",
        "basic": 38,
        "specialized": 52,
        "total": 90,
        "assertions_passed": 4,
        "assertions_total": 4,
        "assertions": [
          {
            "text": "The market-access-value output structure covers required deliverable blocks",
            "result": "PASS",
            "note": "The archived evaluation treated the output structure as aligned with the expected deliverable."
          },
          {
            "text": "Script execution path is available (command exit code is 0)",
            "result": "PASS",
            "note": "Legacy command notes backed the passing execution-path judgment."
          },
          {
            "text": "The output stays within declared skill scope and target objective",
            "result": "PASS",
            "note": "Scope remained controlled in the legacy review for this scenario."
          },
          {
            "text": "Required research safety/boundary guidance is present without overclaims",
            "result": "PASS",
            "note": "The legacy audit kept this scenario within the documented skill boundary."
          }
        ]
      },
      {
        "index": 2,
        "type": "Variant A",
        "label": "Use this skill for academic writing tasks that require explicit assumptions, bounded scope, and a reproducible output format",
        "status": "COMPLETED",
        "status_flag": "PASS",
        "note": "The Use this skill for academic writing tasks that require explicit... scenario completed within the documented Use market access value for academic writing workflows that need structured execution,... boundary.",
        "basic": 36,
        "specialized": 50,
        "total": 86,
        "assertions_passed": 4,
        "assertions_total": 4,
        "assertions": [
          {
            "text": "The market-access-value output structure covers required deliverable blocks",
            "result": "PASS",
            "note": "The archived evaluation treated the output structure as aligned with the expected deliverable."
          },
          {
            "text": "Script execution path is available (command exit code is 0)",
            "result": "PASS",
            "note": "The archived execution trace supported this script-path assertion."
          },
          {
            "text": "The output stays within declared skill scope and target objective",
            "result": "PASS",
            "note": "Scope remained controlled in the legacy review for this scenario."
          },
          {
            "text": "Required research safety/boundary guidance is present without overclaims",
            "result": "PASS",
            "note": "The archived evaluation did not see this scenario drift outside the declared scope."
          }
        ]
      },
      {
        "index": 3,
        "type": "Edge",
        "label": "Use market access value for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries",
        "status": "COMPLETED",
        "status_flag": "PASS",
        "note": "For Use market access value for academic writing workflows that need..., the preserved evidence is lightweight but positive: the packaged validation command behaved as expected.",
        "basic": 35,
        "specialized": 49,
        "total": 84,
        "assertions_passed": 4,
        "assertions_total": 4,
        "assertions": [
          {
            "text": "The market-access-value output structure covers required deliverable blocks",
            "result": "PASS",
            "note": "The legacy audit marked the deliverable structure as passing."
          },
          {
            "text": "Script execution path is available (command exit code is 0)",
            "result": "PASS",
            "note": "The archived execution trace supported this script-path assertion."
          },
          {
            "text": "The output stays within declared skill scope and target objective",
            "result": "PASS",
            "note": "The archived evaluation did not see this scenario drift outside the declared scope."
          },
          {
            "text": "Required research safety/boundary guidance is present without overclaims",
            "result": "PASS",
            "note": "The legacy audit kept this scenario within the documented skill boundary."
          }
        ]
      },
      {
        "index": 4,
        "type": "Variant B",
        "label": "Packaged executable path(s): scripts/main.py",
        "status": "COMPLETED",
        "status_flag": "PASS",
        "note": "The Packaged executable path(s): scripts/main.py scenario completed within the documented Use market access value for academic writing workflows that need structured execution,... boundary.",
        "basic": 34,
        "specialized": 48,
        "total": 82,
        "assertions_passed": 4,
        "assertions_total": 4,
        "assertions": [
          {
            "text": "The market-access-value output structure covers required deliverable blocks",
            "result": "PASS",
            "note": "The archived evaluation treated the output structure as aligned with the expected deliverable."
          },
          {
            "text": "Script execution path is available (command exit code is 0)",
            "result": "PASS",
            "note": "The archived execution trace supported this script-path assertion."
          },
          {
            "text": "The output stays within declared skill scope and target objective",
            "result": "PASS",
            "note": "The archived evaluation did not see this scenario drift outside the declared scope."
          },
          {
            "text": "Required research safety/boundary guidance is present without overclaims",
            "result": "PASS",
            "note": "The legacy audit kept this scenario within the documented skill boundary."
          }
        ]
      },
      {
        "index": 5,
        "type": "Stress",
        "label": "End-to-end case for Scope-focused workflow aligned to: Use market access value for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries",
        "status": "PARTIAL",
        "status_flag": "FAIL",
        "note": "This stress case was mostly intact, but the archived review centered its concern on: The output stays within declared skill scope and target objective.",
        "basic": 31,
        "specialized": 45,
        "total": 76,
        "assertions_passed": 2,
        "assertions_total": 4,
        "assertions": [
          {
            "text": "The market-access-value output structure covers required deliverable blocks",
            "result": "PASS",
            "note": "The archived evaluation treated the output structure as aligned with the expected deliverable."
          },
          {
            "text": "Script execution path is available (command exit code is 0)",
            "result": "PASS",
            "note": "Legacy command notes backed the passing execution-path judgment."
          },
          {
            "text": "The output stays within declared skill scope and target objective",
            "result": "FAIL",
            "note": "The archived review treated this as a scope-control failure."
          },
          {
            "text": "Required research safety/boundary guidance is present without overclaims",
            "result": "FAIL",
            "note": "A boundary-related issue was preserved for this scenario in the legacy evaluation."
          }
        ]
      }
    ]
  },
  "final": {
    "static_weighted": 35.2,
    "dynamic_weighted": 50.2,
    "score": 85,
    "max": 100,
    "grade": "Production Ready",
    "grade_symbol": "*",
    "deployable": true,
    "veto_override": false
  },
  "key_strengths": [
    "Primary routing is Academic Writing with execution mode B",
    "Static quality score is 88/100 and dynamic average is 83.6/100",
    "Assertions and command execution outcomes are recorded per input for human review"
  ],
  "recommendations": [
    {
      "priority": "P1",
      "title": "Stabilize executable path and fallback behavior",
      "observed_in": [
        5
      ],
      "problem": "Some inputs only reached PARTIAL due to execution gaps or weak boundary handling",
      "root_cause": "Example commands are not fully runnable or missing deterministic fallback",
      "fix": "Add validated runnable commands and a strict fallback template for missing parameters and execution errors"
    }
  ]
}


path: references/audit-reference.md
content: # Audit Reference

## Scope

- Skill: `market-access-value`
- Core purpose: Use market access value for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries.
- Use only within the documented workflow and category boundary defined in `SKILL.md`

## Supported Audit Paths

- `python -m py_compile scripts/main.py`
- `python scripts/main.py --help`

## Fallback Boundary

If required inputs are incomplete, the skill should still return:

- the missing required inputs
- the steps that can still be completed safely
- assumptions that need confirmation before execution
- the next checks before accepting the final deliverable


path: scripts/main.py
content: #!/usr/bin/env python3
"""
Market Access Value
Write payer-facing pharmacoeconomic value propositions.
"""

import argparse


class MarketAccessValue:
    """Generate pharmacoeconomic value propositions."""
    
    def generate_value_proposition(self, drug_info):
        """Generate value proposition document."""
        sections = []
        
        sections.append("="*70)
        sections.append("PHARMACOECONOMIC VALUE PROPOSITION")
        sections.append("="*70)
        sections.append("")
        
        # Product Overview
        sections.append("PRODUCT OVERVIEW")
        sections.append("-"*70)
        sections.append(f"Drug Name: {drug_info.get('name', '[Drug Name]')}")
        sections.append(f"Indication: {drug_info.get('indication', '[Indication]')}")
        sections.append(f"Mechanism: {drug_info.get('mechanism', '[Mechanism]')}")
        sections.append("")
        
        # Clinical Value
        sections.append("CLINICAL VALUE")
        sections.append("-"*70)
        sections.append(f"Efficacy: {drug_info.get('efficacy', '[Key efficacy data]')}")
        sections.append(f"Safety: {drug_info.get('safety', '[Safety profile]')}")
        sections.append(f"Unmet Need: {drug_info.get('unmet_need', '[Addressed unmet need]')}")
        sections.append("")
        
        # Economic Value
        sections.append("ECONOMIC VALUE")
        sections.append("-"*70)
        sections.append(f"Cost per QALY: {drug_info.get('cost_per_qaly', '[ICER]')}")
        sections.append(f"Budget Impact: {drug_info.get('budget_impact', '[Budget impact analysis]')}")
        sections.append(f"Cost Offset: {drug_info.get('cost_offset', '[Cost savings vs standard]')}")
        sections.append("")
        
        # Comparative Effectiveness
        sections.append("COMPARATIVE EFFECTIVENESS")
        sections.append("-"*70)
        sections.append(f"vs Standard of Care: {drug_info.get('vs_soc', '[Comparison]')}")
        sections.append(f"Head-to-head Data: {drug_info.get('comparative_data', '[Data]')}")
        sections.append("")
        
        # Patient Outcomes
        sections.append("PATIENT-CENTERED OUTCOMES")
        sections.append("-"*70)
        sections.append(f"Quality of Life: {drug_info.get('qol', '[QoL improvements]')}")
        sections.append(f"Patient Satisfaction: {drug_info.get('satisfaction', '[Patient-reported outcomes]')}")
        sections.append("")
        
        sections.append("="*70)
        
        return "\n".join(sections)


def main():
    parser = argparse.ArgumentParser(description="Market Access Value")
    parser.add_argument("--name", "-n", required=True, help="Drug name")
    parser.add_argument("--indication", "-i", required=True, help="Indication")
    parser.add_argument("--output", "-o", default="value_proposition.txt", help="Output file")
    parser.add_argument("--demo", action="store_true", help="Generate demo")
    
    args = parser.parse_args()
    
    generator = MarketAccessValue()
    
    drug_info = {
        "name": args.name,
        "indication": args.indication,
        "mechanism": "[Mechanism of action]",
        "efficacy": "[Efficacy data]",
        "safety": "[Safety data]",
        "cost_per_qaly": "$[Amount]"
    }
    
    text = generator.generate_value_proposition(drug_info)
    print(text)
    
    with open(args.output, 'w') as f:
        f.write(text)
    print(f"\nSaved to: {args.output}")


if __name__ == "__main__":
    main()


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)