annotate-findings

annotate-findings is a skill for Claude Code from kclemoveki/agentic-skills-eda. It costs 58 tokens per session (1,211 once invoked), scanned A, original, MIT.

A tool that replaces placeholder notes in an executed Jupyter notebook with findings based on its actual outputs. A finding is a conclusion supported by the results produced by the notebook's code.

In plain words
What is it for?
Use it after running a notebook to fill in observation sections with verified findings, or to mark sections where the available output is insufficient.
Why use it?
It prevents analysis notes from claiming numbers or patterns that the code did not actually show.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it after running a notebook to fill in observation sections with verified findings, or to mark sections where the available output is insufficient.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kclemoveki/agentic-skills-eda/annotate-findings
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 kclemoveki/agentic-skills-eda --skill annotate-findings
Clone the repo
git clone --depth 1 https://github.com/kclemoveki/agentic-skills-eda

Made for: Claude Code.

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 annotate-findings

README.md
[![agentmods](https://agentmods.dev/badge/skills/kclemoveki/agentic-skills-eda/annotate-findings/github.svg)](https://agentmods.dev/skills/kclemoveki/agentic-skills-eda/annotate-findings)
Your own site
<a href="https://agentmods.dev/skills/kclemoveki/agentic-skills-eda/annotate-findings"><img src="https://agentmods.dev/badge/skills/kclemoveki/agentic-skills-eda/annotate-findings/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 annotate-findings

Your own site · 80×15
<a href="https://agentmods.dev/skills/kclemoveki/agentic-skills-eda/annotate-findings"><img src="https://agentmods.dev/badge/skills/kclemoveki/agentic-skills-eda/annotate-findings.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,211 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.
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 $0.00058 $0.01211
Opus 5.5 $0.00023 $0.00484
Sonnet 5.5 $0.00012 $0.00242
Haiku 4.5 $0.00006 $0.00121

Measured 2mo ago against content hash b0455fd47150, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

annotate-findings 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 2mo 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/annotate-findings/SKILL.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Annotate Findings

Take the notebook at $ARGUMENTS (which must already have been executed) and replace every placeholder observation cell with real findings derived from the executed outputs of the surrounding code cells.

This skill closes the loop opened by /analyze-dataset (which writes placeholders) and /execute-notebook (which produces real outputs). It eliminates the most common failure of generated notebooks: markdown that claims results that the code never actually proved.

Principle

A finding is only valid if it traces back to an executed output. This skill never invents numbers. If the preceding code cell has no output, or the output cannot be interpreted (binary blobs, image data only), the placeholder gets a clear note saying so — never fabrication.

Step 1 — Validate input

  1. Verify the notebook file exists.
  2. Verify it has been executed: at least one code cell must have non-empty outputs and a non-null execution_count. If the notebook looks pristine (no executions), fail with: Notebook does not appear to have been executed. Run /execute-notebook first.
  3. Locate all markdown cells containing the literal marker <!-- annotate-findings: pending -->. If none are found, report No placeholder cells found — nothing to annotate. and exit cleanly.

Step 2 — For each placeholder, gather context

For each placeholder markdown cell at index i:

  1. Extract the "Qué buscar" bullets from the placeholder (they list what to inspect — use them as the question prompt).
  2. Walk backwards from cell i collecting code cells until you hit either a section header (## N.) or another placeholder. These are the code cells whose outputs feed this observation.
  3. From each gathered code cell, extract:
    • The cell's source (so the skill can read what was computed).
    • All outputs of types stream (stdout/stderr text), execute_result (text/plain representation of last expression), and display_data (descriptions of figures — read the text/plain fallback if present, otherwise note "figure produced").
  4. Concatenate sources + outputs into a context block per placeholder.

Read the full file on GitHub · 90 lines

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. 2mo ago First seen · 90 lines · 0 tokens per session scan A b0455fd47150

Subscribe to this mod's changes

annotate-findings is a skill published in the GitHub repository kclemoveki/agentic-skills-eda (2 stars, last pushed 5mo ago), licensed MIT. It adds 58 tokens to every session and 1,211 once invoked, about $0.0002 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 2026-08-31.

Related

annotate-findings compared with skills from other repositories

annotate-findings next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
annotate-findingskclemoveki/agentic-skills-edaSkill25mo agoMITA58Claude Code
instrument-data-to-allotropeanthropics/knowledge-work-pluginsSkill35k3d agoApache-2.0A123Claude Code
exploratory-data-analysisK-Dense-AI/scientific-agent-skillsSkill56k4d agoMITA83Claude Code
matlabK-Dense-AI/scientific-agent-skillsSkill56k4d agoMITA44Claude Code
phylogeneticsK-Dense-AI/scientific-agent-skillsSkill56k4d agoMITA71Claude Code, Codex
research-engineerdavila7/claude-code-templatesSkill33kyesterdayMITA43Claude Code, Codex
mapping-to-snomedmaziyarpanahi/openmedSkill5.8kyesterdayApache-2.0A205Claude Code