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Fossil

v0.1.0

Semantic failure memory for AI agents. Search past reasoning failures before acting to avoid known mistakes. Record new failures and resolutions after they h...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for heyrtl/fossil.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Fossil" (heyrtl/fossil) from ClawHub.
Skill page: https://clawhub.ai/heyrtl/fossil
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install fossil

ClawHub CLI

Package manager switcher

npx clawhub@latest install fossil
Security Scan
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
Name/description match the implementation: the SKILL.md describes a failure-memory service and the manifest installs an MCP client (npm @openfossil/mcp) and points the agent at a Fossil API — this is proportionate to providing a shared failure-memory service.
Instruction Scope
Runtime instructions are narrowly scoped to searching and recording failures (fossil_search/fossil_record) and to adding an MCP server entry. However, the skill explicitly sends failure descriptions and resolutions to an external API (fossil-api.hello-76a.workers.dev). Those recordings may include sensitive user content (emails, document text, credentials embedded in errors, etc.), so calling these tools can leak sensitive data if not filtered or if the endpoint is untrusted.
Install Mechanism
Install uses an npm package (@openfossil/mcp) invoked via npx, which is a standard mechanism for delivering this kind of tool but does execute remote code at install/run time. The package and its GitHub repo are listed (https://github.com/heyrtl/fossil), which makes auditing possible; using a known npm package is expected but has moderate risk compared to an instruction-only skill.
Credentials
The skill does not request credentials. It asks you to set FOSSIL_API_URL to point at the community API; that is proportionate. However, the payloads the skill will transmit can contain sensitive application data. The lack of required secrets is appropriate, but the privacy/exfiltration risk remains because arbitrary failure text will be sent to an external service.
Persistence & Privilege
The skill is not always-enabled, is user-invocable, and does not request elevated platform privileges or global configuration changes beyond adding an MCP server entry to openclaw.json — this is typical for MCP-based tools and within expected privileges.
Assessment
The skill appears to do what it claims (a shared failure-memory service) but it will transmit failure descriptions/resolutions to an external API and requires running an npm package via npx. Before installing or enabling it: 1) review the @openfossil/mcp npm package and the repository code (https://github.com/heyrtl/fossil) to confirm there are no unexpected behaviors; 2) consider hosting your own Fossil server or pointing FOSSIL_API_URL to a self-hosted endpoint so sensitive content doesn’t go to a public worker; 3) sanitize/filter what you record (strip PII, credentials, user files) or restrict fossil_record to metadata-only; 4) run the MCP binary in a sandboxed environment and pin package versions rather than repeatedly running npx; and 5) if you need stronger guarantees, ask the maintainer for a privacy/security policy or an audit of the package. If you cannot audit the code and the service, treat it as a potential data-leakage vector and limit what gets recorded.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🦴 Clawdis

Install

Node
Bins: openfossil-mcp
npm i -g @openfossil/mcp
latestvk978fv1pap8wfpqnnrgwmgzzbx84qrkb
61downloads
0stars
1versions
Updated 2w ago
v0.1.0
MIT-0

FOSSIL — Semantic Failure Memory

FOSSIL gives your agent a memory for reasoning failures.

Before acting, search for similar past failures. After a failure, record it with the resolution so you never hit the same mistake twice.

The community API at fossil-api.hello-76a.workers.dev is live and free. No API key required. Embeddings run on Cloudflare Workers AI.


Setup

Add to your openclaw.json:

{
  "mcp": {
    "servers": [
      {
        "name": "fossil",
        "command": "npx",
        "args": ["@openfossil/mcp"],
        "env": {
          "FOSSIL_API_URL": "https://fossil-api.hello-76a.workers.dev"
        }
      }
    ]
  }
}

Restart your gateway. FOSSIL tools are now available.


Tools

ToolWhen to use
fossil_searchBefore any non-trivial step — find similar past failures
fossil_recordAfter any failure — capture what went wrong and what fixed it
fossil_getRetrieve a specific fossil by ID
fossil_listBrowse your recent fossil archive

When to search

Call fossil_search before any step involving:

  • Parsing or extracting structured data from LLM output
  • Calling external APIs or tools
  • Multi-step file operations
  • Browser automation
  • Sending messages or emails on behalf of the user
  • Any task domain that has failed before in this workspace

Pass a natural language description of what you are about to attempt. Read the returned resolutions before proceeding.

fossil_search("extracting JSON fields from an invoice document")

When to record

Call fossil_record after any failure, before retrying.

fossil_record(
  situation="sending a reply email to insurance company",
  failure_type="misinterpretation",
  failure="agent replied to wrong thread — matched subject line not sender",
  severity="major",
  resolution_type="prompt_change",
  resolution="added: always match by sender address, not subject line",
  framework="openclaw",
  model="claude-opus-4-5"
)

Failure types

TypeWhen to use
misinterpretationMisread the task or user intent
hallucinated_toolCalled a tool that doesn't exist or wrong signature
format_failureOutput didn't match expected schema or format
context_lossForgot earlier context in a multi-step run
infinite_loopGot stuck in a reasoning or tool-call cycle
premature_terminationDeclared done when the task was incomplete
scope_creepDid more than asked, touched things it shouldn't
ambiguity_paralysisCouldn't proceed due to underspecified input
tool_misuseRight tool, wrong usage or arguments
adversarial_inputExternal input hijacked agent behavior
compounding_errorSmall error amplified across multiple steps

Resolution types

TypeWhen to use
prompt_changeModified the system or user prompt
tool_fixFixed the tool definition or implementation
retryRetrying without changes succeeded
human_overrideHuman intervened directly
context_injectionInjected missing context into the agent window
schema_correctionFixed the output schema or parser
step_decompositionBroke the failing step into smaller steps
input_sanitizationCleaned or validated input before processing

Add to AGENTS.md

## Failure Memory (FOSSIL)

Before any non-trivial task step, call fossil_search with a description
of what you are about to attempt. Read returned resolutions before acting.

After any failure, call fossil_record before retrying. Capture:
- what you were attempting
- what went wrong (use the FOSSIL failure taxonomy)
- what fixed it

This builds a persistent failure memory across all sessions.

Common OpenClaw failure patterns

SituationFailure type
Sent message to wrong contactmisinterpretation
Browser clicked wrong elementtool_misuse
Email reply used wrong tonemisinterpretation
Scheduled task ran at wrong timeformat_failure
Stuck waiting for a responseinfinite_loop
Acted on wrong file or accountscope_creep
Adversarial email hijacked behavioradversarial_input
Stopped mid-task without finishingpremature_termination

Resources

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