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 Zhang-Henry/CoEvoSkills --skill evo-pptx-dangling-titlesgit clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkillsWrote 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/zhang-henry/coevoskills/evo-pptx-dangling-titles)<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/evo-pptx-dangling-titles"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-pptx-dangling-titles/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/zhang-henry/coevoskills/evo-pptx-dangling-titles"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-pptx-dangling-titles.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00055 | $0.00535 |
| Opus 5 | $0.00028 | $0.00267 |
| Sonnet 5 | $0.00011 | $0.00107 |
| Haiku 4.5 | $0.00006 | $0.00053 |
Grade A, and why
evo-pptx-dangling-titles 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 13d 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.
What it actually says
Dangling Paper Title Processor for PPTX
Overview
This skill processes PowerPoint presentations to find "dangling paper titles" - text boxes (non-placeholder shapes) containing paper title text. It reformats them, repositions them, and creates a summary reference slide.
What are Dangling Paper Titles?
In academic presentation slides, paper titles are often placed as free-floating text boxes (not in standard placeholders like Title or Content). These are detected by finding non-placeholder shapes with text frames that contain text.
Operations
- Detect: Find all TEXT_BOX shapes (non-placeholders) with text content
- Reformat: Change font to Arial, size 16pt, color #989596, disable bold
- Resize: Adjust box width so title displays in one line
- Reposition: Center horizontally at bottom of slide
- Reference Slide: Create new slide with "Reference" title and auto-numbered unique titles
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-pptx-dangling-titles/scripts')
from utils import process_pptx, validate_output
# Process the PPTX
result = process_pptx('/root/Awesome-Agent-Papers.pptx', '/root/Awesome-Agent-Papers_processed.pptx')
# Validate the output
errors = validate_output('/root/Awesome-Agent-Papers_processed.pptx')
if errors:
print("VALIDATION FAILED")
else:
print("ALL CHECKS PASSED")
Key Functions
detect_dangling_titles(prs)- Returns list of dicts with slide_index, shape, textestimate_text_width_emu(text, font_size_pt, font_name)- Estimates EMU width for single-line textformat_dangling_title(shape, slide_width, slide_height)- Applies formatting and positioningcollect_unique_titles(dangling_items)- Deduplicates titles preserving ordercreate_reference_slide(prs, titles)- Creates reference slide with numbered listprocess_pptx(input_path, output_path)- End-to-end entry pointvalidate_output(output_path)- Validates the processed file
What ships with it
1 file 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.
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.
- 13d ago First seen · 52 lines · 55 tokens per session scan A e51ba3f2423f
evo-pptx-dangling-titles is a skill published in the GitHub repository Zhang-Henry/CoEvoSkills (66 stars, last pushed 23d ago), licensed Apache-2.0. It adds 55 tokens to every session and 535 once invoked, about $0.0003 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 2026-08-30.
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