Borrowing it
Nothing to install: this file belongs to chemrich/MCPymol. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/chemrich/MCPymol/main/.claude/skills/mcpymol-guide/SKILL.mdgit clone --depth 1 https://github.com/chemrich/MCPymolWrote 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/chemrich/mcpymol/mcpymol-guide)<a href="https://agentmods.dev/skills/chemrich/mcpymol/mcpymol-guide"><img src="https://agentmods.dev/badge/skills/chemrich/mcpymol/mcpymol-guide/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/chemrich/mcpymol/mcpymol-guide"><img src="https://agentmods.dev/badge/skills/chemrich/mcpymol/mcpymol-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00093 | $0.03591 |
| Opus 5 | $0.00046 | $0.01795 |
| Sonnet 5 | $0.00019 | $0.00718 |
| Haiku 4.5 | $0.00009 | $0.00359 |
Grade A, and why
mcpymol-guide 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 — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Driving the mcpymol MCP server
The mcp__mcpymol__* tools talk to a running PyMOL over a socket. Prefer the
high-level tools (fetch_structure, the *_view presets, show/color/
select) over execute_pymol_command — the presets do coloring,
transparency, H-bonds and labels in one call. Reach for
execute_pymol_command only when no dedicated tool covers the need.
Report first, then draw
The presets make pictures; the report tools answer questions with numbers. When the user asks why or how much — what holds this ligand, how big is this interface, where do these differ — run the report and quote the numbers, then apply the matching view if a picture helps. Answering a quantitative question with only a rendering leaves the user to measure it themselves.
| The question | Reach for |
|---|---|
| What is this structure? | structure_info |
| What is the sequence / numbering / where are the gaps? | get_sequence |
| What contacts what, and how tightly? | contact_report -> ligand_view |
| How big is this interface, which residues matter? | interface_report -> interface_view |
| Where do two structures differ? | superposition_view |
| How far / what angle / how much area? | distance, angle, dihedral, sasa, rms_cur |
| Does my selection match anything? | count_atoms |
| Occupancy / altloc / per-atom B-factor? | atom_properties |
contact_report classification is heavy-atom geometry (no hydrogens assumed):
salt bridge <= 4.0 A, H-bond <= 3.5 A between N/O, hydrophobic <= 4.5 A,
ring centroids <= 5.5 A. Report it as such — a "hydrogen bond" here is a
donor-acceptor pair with plausible geometry, not one verified against a
hydrogen. Aromatic detection covers the standard aromatic amino acids only;
ligand rings appear as hydrophobic contacts.
interface_report gives buried surface area per side. Under ~400 A^2 usually
means crystal packing rather than a real interface; over ~1000 A^2 means a
substantial, likely specific association. Say which regime the number is in.
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 · 250 lines · 93 tokens per session scan A 0f9c3ef5e67a
mcpymol-guide is a skill published in the GitHub repository chemrich/MCPymol (15 stars, last pushed 3d ago), licensed MIT. It adds 93 tokens to every session and 3,591 once invoked, about $0.0005 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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