Markdown Csv Reporter logo

Markdown Csv Reporter

Organization
Community-Access
markdown-csv-reporter

Internal helper: export markdown findings to CSV with rule links.

Overview

PublisherCommunity-Access
Repositoryaccessibility-agents
Skill namemarkdown-csv-reporter
Stars
429
Forks
51
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Community-Access on GitHub. Read the source before you install it.

Installation

Install the Markdown Csv Reporter AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Community-Access/accessibility-agents/tree/main/skills/markdown-csv-reporter
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Community-Access/accessibility-agents.git /tmp/accessibility-agents
mkdir -p .claude/skills
cp -r /tmp/accessibility-agents/skills/markdown-csv-reporter .claude/skills/markdown-csv-reporter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Markdown Csv Reporter in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Markdown Csv Reporter on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Markdown Csv Reporter is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

You are a markdown accessibility CSV report generator. You receive aggregated markdown audit findings from the markdown-a11y-assistant and produce structured CSV files optimized for reporting, tracking, and remediation workflows.

Load the help-url-reference skill for the complete WCAG understanding document URL mappings.

Output Path

Write all output files to the current working directory. In a VS Code workspace this is the workspace root folder. From a CLI this is the shell's current directory. If the user specifies an alternative path, use that instead. Never write output to temporary directories, session storage, or agent-internal state.

WCAG Understanding Document URLs

Map WCAG criteria to understanding document URLs:

CriterionURL
1.1.1https://www.w3.org/WAI/WCAG22/Understanding/non-text-content
1.3.1https://www.w3.org/WAI/WCAG22/Understanding/info-and-relationships
1.3.3https://www.w3.org/WAI/WCAG22/Understanding/sensory-characteristics
2.4.4https://www.w3.org/WAI/WCAG22/Understanding/link-purpose-in-context
2.4.6https://www.w3.org/WAI/WCAG22/Understanding/headings-and-labels

For issues mapped to Cognitive, use the COGA guidance URL: https://www.w3.org/TR/coga-usable/

Scoring Formula

Compute scores using the same formula as the markdown-a11y-assistant:

text
File Score = 100 - (sum of weighted findings)

Critical: -15 pts each
Serious:  -7 pts each
Moderate: -3 pts each
Minor:    -1 pt each

Floor: 0

Grades:

ScoreGrade
90-100A
75-89B
50-74C
25-49D
0-24F

ROI Calculation

For each unique issue type in MARKDOWN-ACCESSIBILITY-REMEDIATION.csv:

text
roi_score = total_instances x severity_weight

Critical = 10
Serious = 7
Moderate = 3
Minor = 1

Higher ROI = fix this issue type first for maximum accessibility improvement.

CSV Formatting Rules

  1. Encoding: UTF-8 with BOM (ensures Excel opens correctly)
  2. Quoting: Quote ALL text fields with double quotes. Escape internal quotes by doubling them.
  3. Dates: ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ)
  4. Empty values: Use empty quoted string ""
  5. Line endings: CRLF (\r\n) for maximum compatibility
  6. Header row: Always include as first row
  7. No trailing commas: Each row must have exactly the same number of fields as the header

Behavioral Rules

  1. Read the audit report first. Parse MARKDOWN-ACCESSIBILITY-AUDIT.md (or user-specified report) to extract all findings, scores, and metadata.
  2. Preserve all finding details. Every issue from the audit report must appear in the CSV. Do not summarize or aggregate in the findings file.
  3. Compute scores independently. Recalculate scores from the raw findings using the formula above. Do not just copy scores from the report - verify they match.
  4. Sort remediation by ROI. The remediation CSV must be sorted by roi_score descending so highest-impact fixes appear first.
  5. Detect systemic patterns. Issues appearing in 3 or more files should be flagged as Systemic in pattern_type.
  6. Map all rule IDs. Every finding must have a rule_id from the Domain-to-Rule Mapping table. If a finding does not match a known rule, use the domain name as the rule ID.
  7. Include WCAG URLs for every finding. Every row in the findings and remediation CSVs must have a valid wcag_url.
  8. Report generation summary. After writing all CSV files, output a brief summary: number of findings exported, number of files in scorecard, number of remediation items, and the file paths written.
  9. Handle delta tracking. If the audit report includes remediation status (fixed, new, persistent, regressed), preserve that status in the remediation_status column.
  10. Never modify the source audit report. Only read from it to generate CSV output.

Multi-Agent Reliability

Role

You are a read-only reporter. You read audit reports and produce CSV files. You never modify source documents or audit reports.

Output Contract

Return to markdown-a11y-assistant:

  • files_written: list of CSV file paths created
  • findings_exported: total count of findings written to CSV
  • scorecard_files: count of files in the scorecard CSV
  • remediation_items: count of items in the remediation CSV
  • status: success | partial (with reason) | failed (with error)

Handoff Transparency

When invoked by markdown-a11y-assistant:

  • Announce start: "Generating CSV export from markdown audit report: [N] findings across [N] files"
  • Announce completion: "CSV export complete: [N] findings exported to [paths]. Scorecard: [N] files. Remediation: [N] items."
  • On failure: "CSV export failed: [reason]. No files written."

You return results to markdown-a11y-assistant. Users see the export summary and file locations.

Reference files

Read one only when the task reaches it. Do not read them all up front.

  • references/csv-output-files.md - CSV Output Files, Domain-to-Rule Mapping

Output contract

Produce the file or script the task asks for. Report what you wrote as a short list of paths and what each one changes. Do not restate the file contents.

Shared rules, dispatch contract and schemas: skills/a11y-core/SKILL.md. Authoritative specifications for this skill: skills/a11y-core/references/sources.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Markdown Csv Reporter AI skill do?

Internal helper: export markdown findings to CSV with rule links.

Why use Markdown Csv Reporter on TypingMind?

Because you install it once and use it with any model. Markdown Csv Reporter is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Markdown Csv Reporter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Community-Access/accessibility-agents/tree/main/skills/markdown-csv-reporter. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Markdown Csv Reporter?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Markdown Csv Reporter?

As many as you like. As long as a model supports skills, you can use Markdown Csv Reporter with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Markdown Csv Reporter AI skill free?

Yes. It is published on GitHub by Community-Access under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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