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Agent skill

Kayba Stage 1 API Analysis

by kayba-ai in kayba-ai/agentic-context-engine

Fetch pre-computed insights from the Kayba API and build a structured summary.

Apache-2.0Auto-check passedAgent Workflows

Install Kayba Stage 1 API Analysis

skills CLI
$ npx skills add kayba-ai/agentic-context-engine --skill kayba-stage-1-api-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install kayba-ai/agentic-context-engine kayba-stage-1-api-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/kayba-ai/agentic-context-engine.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/kayba-pipeline/stage-1-api-analysis .claude/skills/kayba-stage-1-api-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
kayba-stage-1-api-analysis
GitHub stars
2.6k
Token cost
~1.1k tokens
SKILL.md length
422 words
Files
1
Skills in repo
8
Repo updated
First seen
Licence
Apache-2.0

At a glance

Fetch pre-computed insights from the Kayba API and build a structured summary.

  • Generation — analysis is assumed to already exist
  • SKILL.md covers Inputs, Process, Error handling and Outputs
  • Needs KAYBA_API_KEY
  • The user says run stage 1

What it does

Kayba Stage 1 API Analysis is an agent skill from kayba-ai/agentic-context-engine. Fetch pre-computed insights from the Kayba API and build a structured summary. Does NOT upload traces or trigger generation — analysis is assumed to already exist. Trigger when the user says "run stage 1", "get insights", "fetch skills", "kayba analyze", or when invoked by the kayba-pipeline orchestrator. Requires the kayba CLI to be installed and KAYBAAPIKEY to be set.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows. The repository describes itself as: 🧠 Make your agents learn from experience. Now available as a hosted solution at kayba.ai. The licence is Apache-2.0.

When your agent uses it

  • Generation — analysis is assumed to already exist
  • The user says run stage 1
  • Invoked by the kayba-pipeline orchestrator

Example prompts

  • “run stage 1”
  • “get insights”
  • “fetch skills”
  • “/kayba-stage-1-api-analysis”

Requirements

  • A credential in KAYBA_API_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit 3a31983. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • KAYBA_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Kayba Stage 1 API Analysis loads about 1.1k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 422 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from kayba-ai/agentic-context-engine at commit 3a31983, republished under its Apache-2.0 licence (© kayba-ai). 422 words, ~1,061 tokens.

Download SKILL.mdSave it as .claude/skills/kayba-stage-1-api-analysis/SKILL.md (or your agent's skills folder).
name
kayba-stage-1-api-analysis
description
Fetch pre-computed insights from the Kayba API and build a structured summary. Does NOT upload traces or trigger generation — analysis is assumed to already exist. Trigger when the user says "run stage 1", "get insights", "fetch skills", "kayba analyze", or when invoked by the kayba-pipeline orchestrator. Requires the kayba CLI to be installed and KAYBA_API_KEY to be set.

Stage 1: Kayba API Analysis (Fetch-Only Mode)

Fetch pre-computed insights from the Kayba API. Traces have already been uploaded and analyzed — this stage only pulls results.

Inputs

  • TRACES_FOLDER — passed by the orchestrator but ignored in this stage. Traces are already uploaded and analyzed on the Kayba side. Do NOT upload, validate, or read trace files.

Process

Step 1: Setup

Ensure eval/ directory exists at the project root.

Step 2: Fetch insights
kayba insights list --json > eval/insights.json

If kayba is not found in PATH, search common locations (.venv/bin/kayba, project virtualenvs). If found, use the full path. If not found anywhere, report the error and stop.

If KAYBA_API_KEY is not set, report the error and stop.

Step 3: Insight quality gate

Read eval/insights.json and run quality checks before building the summary:

  1. Empty check: if the insights array is empty (0 insights returned), report this as a warning. Write a minimal summary noting "0 insights generated" and stop — downstream stages cannot proceed without insights.
  2. Duplicate detection: compare insight content fields pairwise. If two insights cover substantially the same behavior (same section, overlapping evidence traces, similar corrective action), flag them as potential duplicates in the summary. Do not remove them — just annotate.
  3. Evidence coverage: for each insight, check if the evidence field references specific traces (e.g., "task_7 turn 4"). Insights with no trace-specific evidence are lower quality — flag as "low-evidence" in the summary.
  4. Vote signal: insights with status: "accepted" and helpful > 0 have been human-validated. Insights with status: "new" and helpful: 0, harmful: 0 are unvalidated — note this distinction in the summary.

Log the quality gate result: "Insight quality: {total} insights, {accepted} accepted, {new_unvalidated} unvalidated, {duplicates} potential duplicate pairs, {low_evidence} low-evidence"

Show full SKILL.md (146 more words)Show less
Step 4: Build structured summary

Extract a structured summary of each insight:

  • Insight ID and title/summary (use the section field as the title)
  • Status
  • Evidence citations — specific trace references, error strings, behavioral patterns the reflector identified
  • Justification / reasoning chain — the reflector's full analysis of why this is a real pattern
  • Confidence score if available
  • Helpful/harmful counts if available
  • Quality flags from Step 3 (potential duplicate, low-evidence, unvalidated)

Write the structured summary to eval/stage1_insights_summary.md using this format:

markdown
# Kayba Insights Summary

Generated from: Kayba API (pre-computed analysis)
Total insights: N
Quality: {accepted} accepted, {unvalidated} unvalidated, {duplicate_pairs} potential duplicate pairs, {low_evidence} low-evidence

## Insight: [ID] — [section title]
**Status:** [status] [quality flags if any, e.g., "[potential duplicate with ID]", "[low-evidence]", "[unvalidated]"]
**Confidence:** [score if available]
**Evidence:**
- [citation 1 — trace reference, error string, or behavioral pattern]
- [citation 2]
**Justification:** [reflector's reasoning for why this is a real pattern]
**Helpful/Harmful:** [counts if available]

---
[repeat for each insight]

Error handling

  • If kayba is not found in PATH or common locations, report the error and stop
  • If KAYBA_API_KEY is not set, report the error and stop
  • If kayba insights list fails (network error, auth error), report the error and stop
  • If 0 insights are returned, write a minimal summary and stop — downstream stages need insights

Outputs

  • eval/insights.json — raw API response
  • eval/stage1_insights_summary.md — structured summary with quality annotations for downstream stages

© kayba-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/kayba-pipeline/stage-1-api-analysis of kayba-ai/agentic-context-engine.

Open the folder on GitHubat commit 3a31983

Compare with similar skills

Kayba Stage 1 API Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Grillingpietheinstrengholt/rssmonster56431 repos~510Automated safety check: PassMIT
CodeGraph Agent Evalcolbymchenry/codegraph74k—~950Automated safety check: PassMIT
Improvefossasia/eventyay-interpretation1.6k10 repos~3.7kAutomated safety check: WarnMIT
Loop Change Verifiercobusgreyling/loop-engineering11k1 repos~709Automated safety check: PassMIT

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Categories

Questions about Kayba Stage 1 API Analysis

What does Kayba Stage 1 API Analysis do?

Fetch pre-computed insights from the Kayba API and build a structured summary. Kayba Stage 1 API Analysis is an agent skill from kayba-ai/agentic-context-engine. Fetch pre-computed insights from the Kayba API and build a structured summary.

When should I use Kayba Stage 1 API Analysis?

Kayba Stage 1 API Analysis fits situations like: generation — analysis is assumed to already exist; the user says run stage 1; invoked by the kayba-pipeline orchestrator.

How do I install Kayba Stage 1 API Analysis in Claude Code?

Run `npx skills add kayba-ai/agentic-context-engine --skill kayba-stage-1-api-analysis -a claude-code`. Or copy the skill folder (.claude/skills/kayba-pipeline/stage-1-api-analysis in kayba-ai/agentic-context-engine) into .claude/skills/kayba-stage-1-api-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Kayba Stage 1 API Analysis in Codex?

Run `npx skills add kayba-ai/agentic-context-engine --skill kayba-stage-1-api-analysis -a codex`. Or copy the skill folder (.claude/skills/kayba-pipeline/stage-1-api-analysis in kayba-ai/agentic-context-engine) into .agents/skills/kayba-stage-1-api-analysis in your project. Codex loads it when a task matches its description.

Can I use Kayba Stage 1 API Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add kayba-ai/agentic-context-engine --skill kayba-stage-1-api-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kayba-stage-1-api-analysis, .gemini/skills/kayba-stage-1-api-analysis, .github/skills/kayba-stage-1-api-analysis and .opencode/skills/kayba-stage-1-api-analysis in your project.

What does Kayba Stage 1 API Analysis need to run?

Going by SKILL.md and its folder, Kayba Stage 1 API Analysis needs credentials named KAYBA_API_KEY. Our summary lists: A credential in KAYBA_API_KEY.

Does Kayba Stage 1 API Analysis access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Kayba Stage 1 API Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Kayba Stage 1 API Analysis use?

Kayba Stage 1 API Analysis is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Kayba Stage 1 API Analysis use?

About 1.1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Kayba Stage 1 API Analysis?

Skills that share tags, products or a category with Kayba Stage 1 API Analysis: Diagnosing Superpowers Sessions (obra/superpowers, 297k stars), Grilling (pietheinstrengholt/rssmonster, 564 stars), CodeGraph Agent Eval (colbymchenry/codegraph, 74k stars) and Improve (fossasia/eventyay-interpretation, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Kayba Stage 1 API Analysis?

kayba-ai (a GitHub organization) maintains it in kayba-ai/agentic-context-engine, which has 2,590 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on September 24, 2026.

Source: kayba-ai/agentic-context-engine on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.