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.
npx skills add adilkalam/orca --skill ascii-tablesgit clone --depth 1 https://github.com/adilkalam/orcaWrote 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.
[](https://agentmods.dev/skills/adilkalam/orca/ascii-tables)<a href="https://agentmods.dev/skills/adilkalam/orca/ascii-tables"><img src="https://agentmods.dev/badge/skills/adilkalam/orca/ascii-tables/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.
<a href="https://agentmods.dev/skills/adilkalam/orca/ascii-tables"><img src="https://agentmods.dev/badge/skills/adilkalam/orca/ascii-tables.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00013 | $0.01444 |
| Opus 5 | $0.00006 | $0.00722 |
| Sonnet 5 | $0.00003 | $0.00289 |
| Haiku 4.5 | $0.00001 | $0.00144 |
Grade A, and why
table 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ASCII Table Alignment Skill
THE PROBLEM
LLMs cannot align markdown tables correctly because:
- Token-by-token generation - No spatial awareness during output
- Variable character widths - Even in monospace fonts:
- CJK characters = 2 cells wide
- Emoji = variable width
- Combining characters = 0 width
- No backtracking - Cannot adjust previous output based on later content
No amount of prompt engineering fixes this. The problem is fundamental to how LLMs generate text.
THE SOLUTION
Two-phase approach:
- Generation Phase (LLM) - Focus on content, not alignment
- Formatting Phase (Script) - wcwidth-based column alignment
MANDATORY PROTOCOL
When generating markdown tables, you MUST follow this protocol:
Step 1: Generate Table Content
Focus on correctness and completeness. Do NOT waste effort on manual alignment.
| Column A | Column B | Column C |
|---|---|---|
| Short | Much longer content here | X |
| Another row | Data | More data |
Step 2: Run Formatter (MANDATORY)
After generating any markdown table, you MUST run:
python3 ~/.claude/scripts/md-table-formatter.py /path/to/file.md
Or for stdin/stdout:
echo "table content" | python3 ~/.claude/scripts/md-table-formatter.py
Step 3: Verify Output
Check stderr for verification report:
TABLE_FORMAT_CHECK:
- Tables processed: N
- Column widths: [W1, W2, W3, ...]
- Status: ALIGNED
GENERATION GUIDELINES
When creating table content:
- Use simple separators -
|---|---|---|not|:---:|:---:|:---:| - Content first - Get the data right, formatting comes later
- One table at a time - Easier to verify
- Preserve semantics - Formatter only adjusts spacing
What the Formatter Does
- Calculates display width of each cell using wcwidth
- Finds maximum width for each column
- Pads cells with spaces to align columns
- Normalizes separator rows
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.
- 9d ago First seen · 255 lines · 13 tokens per session scan A 470e7954cc51
table is a skill published in the GitHub repository adilkalam/orca (2 stars, last pushed 1mo ago), licensed MIT. It adds 13 tokens to every session and 1,444 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
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