jairorodriguezarias/siesta/kb-manager

Name: kb-manager
Author: jairorodriguezarias

Claude Code and agent skill by jairorodriguezarias/siesta

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Manages the JSON-based knowledge graph with progressive disclosure. Use when reading or writing decisions, blockers, learnings, or consultations to the KB. Provides query, append, and link operations.

Install

npx vskill@latest install jairorodriguezarias/siesta/kb-manager

SKILL.md

KB Manager

Manages the file-based JSON knowledge graph. Nodes store typed information (decisions, blockers, learnings, consultations) with summary + detail for progressive disclosure. Edges store typed relationships between nodes.

Pipeline Tool Boundaries

When tools are disabled (consultant, proxy or learner), use the KB context provided in the prompt and return the requested text protocol. The CLI examples below are reference operations for an operator or a tool-enabled role; do not narrate their execution. Python persists protocol decisions, completion records and parsed learnings. A worker must never create an "Issue #N completed" node or alter checkpoints to bypass Python's test gate.

When to Use

Before executing an issue: query relevant KB context
After making a decision: log it to KB
After resolving a blocker: log resolution to KB
After learning something: log it to KB
NOT for: trivial changes that don't affect future work

KB Structure

json

{
  "nodes": [
    {
      "id": "n1234_5678",
      "type": "decision|blocker|learning|consultation|spec|issue",
      "summary": "One-line summary (loaded first)",
      "detail": "Full reasoning (loaded on drill-down)",
      "created_at": "2024-01-01T00:00:00Z"
    }
  ],
  "edges": [
    {
      "from": "n1234_5678",
      "to": "n5678_9012",
      "type": "applied_to|caused_by|resolved_by|depends_on|parent_of|consulted_for|learned_from",
      "created_at": "2024-01-01T00:00:00Z"
    }
  ]
}

Progressive Disclosure

Level 1 — Summary only (default, cheap):

bash

python3 -m pipeline.kb query kb/graph.json --summary-only
# Returns: [{id, type, summary}] — minimal tokens

Level 2 — Full node (on demand, when an issue needs detail):

bash

python3 -m pipeline.kb get-node kb/graph.json n1234_5678
# Returns: full node with detail field

Level 3 — Filtered by type (when you need all decisions, or all blockers):

bash

python3 -m pipeline.kb query kb/graph.json --type decision --summary-only

Operations

Query (read)

bash

# All summaries (cheapest)
python3 -m pipeline.kb query kb/graph.json --summary-only
 
# All decisions only
python3 -m pipeline.kb query kb/graph.json --type decision --summary-only
 
# Full detail for a specific node
python3 -m pipeline.kb get-node kb/graph.json n1234_5678
 
# List everything (quick overview)
python3 -m pipeline.kb list-all kb/graph.json

Append Node (write)

bash

# Log a decision
python3 -m pipeline.kb append-node kb/graph.json "decision" \
  "Used argparse for CLI parsing" \
  "Qwen chose argparse over click for zero dependencies. Click requires extra pip install."
 
# Log a blocker
python3 -m pipeline.kb append-node kb/graph.json "blocker" \
  "Timer drift on long sessions" \
  "time.time() drifts. Fixed by using time.monotonic(). Suggested by the consultant."
 
# Log a learning
python3 -m pipeline.kb append-node kb/graph.json "learning" \
  "Always use monotonic for timers" \
  "time.time() is affected by system clock changes. time.monotonic() is immune."
 
# Log a consultation
python3 -m pipeline.kb append-node kb/graph.json "consultation" \
  "Consultant advised on timer drift" \
  "Worker asked about timer drift. Consultant recommended time.monotonic(). Confidence: high."

Append Edge (link)

bash

# Decision was applied to an issue
python3 -m pipeline.kb append-edge kb/graph.json n1234_5678 n9012_3456 applied_to
 
# Blocker was resolved by a consultation
python3 -m pipeline.kb append-edge kb/graph.json n3456_7890 n5678_9012 resolved_by
 
# Learning was learned from a blocker
python3 -m pipeline.kb append-edge kb/graph.json n5678_9012 n3456_7890 learned_from

Initialize (new project)

bash

python3 -m pipeline.kb init-project kb/graph.json

Common Rationalizations

Rationalization	Reality
"I'll remember this decision"	You won't. The KB is the memory. Log it.
"Detail is too long to write"	Summary is enough for Level 1. Detail can be long — it loads on demand.
"I don't need to query the KB, I know the context"	Past decisions affect current work. Always query summaries first.
"This is too small to log"	If a future issue could benefit, log it. Small decisions compound.

Red Flags

Writing detail without a summary (summary is the progressive disclosure entry point)
Creating nodes without edges (orphan nodes are hard to discover)
Loading full detail when summaries would suffice (wastes context tokens)
Not initializing a fresh KB per project (cross-project contamination)

Verification

[ ] Every decision has both summary and detail
[ ] Blockers have resolution edges to what resolved them
[ ] Consultations are linked to the issue they were for
[ ] Summaries are one line, under 100 characters
[ ] Queries start with --summary-only before drilling into detail

Security

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Model reviewPassed

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Quality evaluation

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Source

SKILL.md in the repositoryCheckingfactory/skills/kb-manager/SKILL.md

Popularity

Repository stars: 79
Repository forks: 18
7-day trend score: 22

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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