markdown-csv-reporter

markdown-csv-reporter is a skill for Claude Code, Codex from Community-Access/accessibility-agents. It costs 18 tokens per session (1,426 once invoked), scanned A, original, MIT.

An exporter that turns Markdown accessibility findings into structured CSV reports. The reports include issue severity, accessibility criteria, linter references, and suggested remediation.

In plain words
What is it for?
Use it to export accessibility audit results for spreadsheets, tracking, and remediation workflows.
Why use it?
Audit results are harder to track when they remain only in prose. CSV files make findings easier to sort, report, and manage as work items.

Skill for Claude CodeCodex

Written for Claude Code and Codex: disable-model-invocation in frontmatter, but also agents/openai.yaml present.

Part of the accessibility-agents plugin — 108 skills, 6 hooks shipped together

Good fit Use it to export accessibility audit results for spreadsheets, tracking, and remediation workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/community-access/accessibility-agents/markdown-csv-reporter
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Community-Access/accessibility-agents --skill markdown-csv-reporter
Clone the repo
git clone --depth 1 https://github.com/Community-Access/accessibility-agents

Made for: Claude Code, Codex.

Or install accessibility-agents, the plugin that ships this one along with the rest of its 108 skills, 6 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for markdown-csv-reporter

README.md
[![agentmods](https://agentmods.dev/badge/skills/community-access/accessibility-agents/markdown-csv-reporter/github.svg)](https://agentmods.dev/skills/community-access/accessibility-agents/markdown-csv-reporter)
Your own site
<a href="https://agentmods.dev/skills/community-access/accessibility-agents/markdown-csv-reporter"><img src="https://agentmods.dev/badge/skills/community-access/accessibility-agents/markdown-csv-reporter/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for markdown-csv-reporter

Your own site · 80×15
<a href="https://agentmods.dev/skills/community-access/accessibility-agents/markdown-csv-reporter"><img src="https://agentmods.dev/badge/skills/community-access/accessibility-agents/markdown-csv-reporter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,426 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.01426
Opus 5.5 $0.00007 $0.00570
Sonnet 5.5 $0.00004 $0.00285
Haiku 4.5 $0.00002 $0.00143

Measured 1mo ago against content hash 31e28e92e3b2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

markdown-csv-reporter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/markdown-csv-reporter/SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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:

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

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:

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

ROI Calculation

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

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

Read the full file on GitHub · 140 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago Changed · -73 lines · -26 tokens per session 31e28e92e3b2
  2. 1mo ago First seen · 213 lines · 44 tokens per session scan A 419f9d487239

Subscribe to this mod's changes

markdown-csv-reporter is a skill published in the GitHub repository Community-Access/accessibility-agents (428 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 1,426 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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