pathfind

pathfind is a skill for Claude Code from kangig94/coral. It costs 15 tokens per session (2,809 once invoked), scanned A, original, MIT.

A problem-discovery workflow for turning several symptoms into a ranked list of possible directions, then passing the result to planning.

In plain words
What is it for?
Use it to sort user-reported problems, identify patterns across systems, record the findings in a project plan, and choose what to investigate first.
Why use it?
It helps when you know what is going wrong but do not yet know what to build. It groups related symptoms and highlights likely shared causes before planning starts.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the coral plugin — 12 skills, 10 agents shipped together

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.

agentmods
npx agentmods add skills/kangig94/coral/pathfind
Any agent
npx skills add kangig94/coral --skill pathfind
Clone the repo
git clone --depth 1 https://github.com/kangig94/coral

Made for: Claude Code.

Or install coral, the plugin that ships this one along with the rest of its 12 skills, 10 agents.

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 pathfind

README.md
[![agentmods](https://agentmods.dev/badge/skills/kangig94/coral/pathfind.svg)](https://agentmods.dev/skills/kangig94/coral/pathfind)
Your own site
<a href="https://agentmods.dev/skills/kangig94/coral/pathfind"><img src="https://agentmods.dev/badge/skills/kangig94/coral/pathfind.svg" alt="Measured on agentmods" height="20"></a>
Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,809 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00015 $0.02809
Opus 5 $0.00008 $0.01404
Sonnet 5 $0.00003 $0.00562
Haiku 4.5 $0.00002 $0.00281

Measured 5d ago against content hash f4eb239e6ca6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

pathfind 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 5d 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.

clients/skills/pathfind/SKILL.md · 309 lines

How it starts

The opening of the file, as written. The whole thing — 309 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pathfinding — Symptom-to-Direction Discovery

Pathfind always produces a ranked direction list and hands off to /preplan. This is the defining contract.

Step 1 — Intake

Parse the user's problem descriptions from args.

  • Clarification guardrail: If fewer than 2 concrete symptoms are identified, ask clarifying questions. Max 2 clarification rounds, then proceed with caveats noted in the artifact.

  • Derive {topic} from the user's input as English kebab-case (e.g. "API slow, DB limits, user complaints" -> api-performance)

  • Create artifact file: CORAL_PROJECT/plans/pathfind-{topic}.md with header:

    # Pathfind: {topic}
    
    ## Problems
    [User's original problem descriptions]
    

Step 2 — Triage

Cluster related problems by shared patterns, systems, or root cause indicators.

  • Group symptoms that likely share a common cause
  • Identify cross-cutting symptoms that appear in multiple clusters
  • Single-symptom input: treat as one cluster, note limited clustering in artifact

Write to artifact:

## Problem Clusters
| Cluster | Symptoms | Pattern |
|---------|----------|---------|
| {name}  | {list}   | {shared pattern or system} |

Step 3 — Investigate

Bug detection: Before investigation, check for bug-type symptoms:

  • Detection: symptoms containing error output, stack traces, or "X crashes/fails when Y"
  • If bug-type symptoms found:
    • Suggest: "These symptoms look like code bugs — consider /analyze or /bugfix for: {bug symptoms}"
    • If all symptoms are bugs: exit with delegation suggestion
    • If mixed: continue pathfind with remaining non-bug symptoms

Investigation path — choose based on whether relevant code exists:

A. Codebase exists (clusters reference existing systems, files, or modules):

Agent({ subagent_type: "coral:scanner",
  prompt: "Investigate these problem clusters using Approach B (Process Investigation).
    Scope: systems and modules related to these clusters only — do NOT perform a full project scan.
    Clusters: {cluster list with symptoms}
    Work dir: {work_dir}
    Output: root cause candidates per cluster with file:line evidence." })

If scanner fails: retry once, then proceed with direct codebase reads.

B. No codebase / process-only problems (clusters are about workflow, team, tooling, or greenfield): Skip scanner. Pathfind derives root causes directly from triage clusters through reasoning. Use web search for prior art if the problem domain is unfamiliar.

Map findings to problem clusters — derive root causes:

  • Each root cause must trace back to one or more clusters
  • Each root cause must have evidence (file:line, observation, or reasoning chain)

Write to artifact:

## Root Causes
| # | Root Cause | Source Cluster | Evidence |
|---|-----------|----------------|----------|

Step 4 — Prescribe

Generate directions through orthogonal lanes — one direction per lane, not multiple per root cause. Lanes guarantee divergence because each forces a different mechanism.

Derive lanes from the problem domain. Each lane must represent a fundamentally different mechanism — not a variation. Aim for 3-5 lanes.

Examples by domain:

Code/architecture problems:

Lane Perspective
local_repair Minimal in-place fix, no architectural change
boundary_redesign Move responsibility across interfaces or ownership lines
representation_change Change state, data model, or information shape
probe_first Add instrumentation or experiments before committing to a fix
workflow_guardrail Solve via tests, process, tooling, or validation

Read the full file on GitHub · 309 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. 5d ago First seen · 309 lines · 15 tokens per session scan A f4eb239e6ca6

Subscribe to this mod's changes

pathfind is a skill published in the GitHub repository kangig94/coral (11 stars, last pushed 3d ago), licensed MIT. It adds 15 tokens to every session and 2,809 once invoked, about $0.0001 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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