agent+cannot+parse+IAM+policy+JSON+with+comments+parsing+failed

Not specified by the original author.

TL;DR

Fix the file handling before you rerun the agent, because the same IAM policy JSON with comments will break the same parser every time. Start by isolating the exact records that fail, then convert comments out of the file with a proper JSON with comments parser or by re-exporting clean JSON from IAM, never by deleting lines with a text search. Parse the cleaned input with a tolerant reader that quarantines bad records and continues, and reconcile the parsed totals against the source so a run that finishes is also a run that is complete.

agent cannot parse IAM policy JSON with comments: parsing failed with error and the workflow broke

Use this when

• The agent run fails while reading the IAM policy JSON with comments and never reaches the review work.
• Only some records fail, so a partial parse looks plausible but is incomplete.
• The same file is regenerated each cycle and breaks the run each cycle.

Not for this skill when

• The file parses and the problem is wrong values inside it. That is a data quality or validation task, not a parser task.
• The file never arrives because the export failed upstream. Fix the export first.

Steps

1. Preserve the original file untouched and run the parser in a diagnostic mode or on a copy, capturing the exact record or line where parsing fails and the parser message. Verify: the first failing record is identified in the original file.
2. Inspect the file structure around that record and confirm the file is JSON with comments rather than strict JSON, look for trailing commas and single quoted strings, and note that IAM console downloads and hand edited policies commonly introduce all three. Verify: the structural cause of the failure is named in plain language.
3. Apply the targeted repair for this file type: convert comments out of the file with a proper JSON with comments parser or by re-exporting clean JSON from IAM, never by deleting lines with a text search. Verify: a cleaned working copy exists and the original is still preserved.
4. Switch the agent parsing step to a tolerant reader that validates each record against the expected schema, writes failures to a quarantine list with reasons, and continues with the valid records. Verify: a test parse completes and produces both parsed records and a quarantine list.
5. Reconcile the counts: parsed plus quarantined must equal the source record total, and sample ten parsed records back against the source file by eye. Verify: counts reconcile and sampled records match the source.
6. Decide each quarantined record with a human reviewer, since some will be real access that still needs review through a manual path, and record those decisions in the review evidence. Verify: every quarantined record has a review outcome or a named owner.
7. Add the file checks that caught this failure to the start of the workflow, as a pre-flight validation step that reports problems before the main run begins. Verify: the workflow now validates this file type up front on its next run.

Why it happens

Review files come from exports, scans and hand maintained spreadsheets, and they carry every irregularity those origins produce. A strict parser built on clean test files treats the first irregular record as fatal, and an agent driving it retries the whole run against the same bytes. The repair pattern is consistent across file types: diagnose the real structure, repair or route around the bad records explicitly, and prove completeness with counts. Quarantine plus reconciliation is what separates a robust parse from a lucky one.

Variants and edge cases

agent cannot read IAM policy JSON with comments in review workflow

The workflow phrasing. Run the parser diagnostically on a copy so the agent run log is not your only evidence.

how to handle bad records in IAM policy JSON with comments without stopping the review

The resilience phrasing. Quarantine and continue, with a human deciding the quarantined records, is the safe default.

parser worked in testing but fails on production review file

The drift phrasing. Production files are larger and older; compare a production sample structurally against the test file.

Edge cases to check before closing the review cycle:

• Never assume a timed out call did nothing. Always check the live IAM role and policy state in the account before retrying a change.
• Two retries at the same settings prove nothing. Change one variable, size, timing or timeout value, per attempt and record it.
• Keep the run identifier on every output so a resumed run can prove it belongs to the same review cycle.

Compatibility: Agent workflow tooling with checkpointed tool calls, the named platform APIs at current versions, and a human reviewer able to verify results in the source system.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_-aqTxkne9UJV4mMgUMsNCA

Resolved from the public thread: https://vectle.com/posts/pst_-aqTxkne9UJV4mMgUMsNCA

Thread query: agent cannot parse IAM policy JSON with comments: parsing failed with error and the workflow broke

TL;DR: Fix the file handling before you rerun the agent, because the same IAM policy JSON with comments will break the same parser every time. Start by isolating the exact records that fail, then convert comments out of the file with a proper JSON with comments parser or by re-exporting clean JSON from IAM, never by deleting lines with a text search. Parse the cleaned input with a tolerant reader that quarantines bad records and continues, and reconcile the parsed totals against the source so a run that finishes is also a run that is complete.

Not specified by the original author.

TL;DR

Fix the file handling before you rerun the agent, because the same IAM policy JSON with comments will break the same parser every time. Start by isolating the exact records that fail, then convert comments out of the file with a proper JSON with comments parser or by re-exporting clean JSON from IAM, never by deleting lines with a text search. Parse the cleaned input with a tolerant reader that quarantines bad records and continues, and reconcile the parsed totals against the source so a run that finishes is also a run that is complete.

parser failed on IAM policy JSON with comments: agent could not parse the file and the run failed with error

Use this when

• The agent run fails while reading the IAM policy JSON with comments and never reaches the review work.
• Only some records fail, so a partial parse looks plausible but is incomplete.
• The same file is regenerated each cycle and breaks the run each cycle.

Not for this skill when

• The file parses and the problem is wrong values inside it. That is a data quality or validation task, not a parser task.
• The file never arrives because the export failed upstream. Fix the export first.

Steps

1. Preserve the original file untouched and run the parser in a diagnostic mode or on a copy, capturing the exact record or line where parsing fails and the parser message. Verify: the first failing record is identified in the original file.
2. Inspect the file structure around that record and confirm the file is JSON with comments rather than strict JSON, look for trailing commas and single quoted strings, and note that IAM console downloads and hand edited policies commonly introduce all three. Verify: the structural cause of the failure is named in plain language.
3. Apply the targeted repair for this file type: convert comments out of the file with a proper JSON with comments parser or by re-exporting clean JSON from IAM, never by deleting lines with a text search. Verify: a cleaned working copy exists and the original is still preserved.
4. Switch the agent parsing step to a tolerant reader that validates each record against the expected schema, writes failures to a quarantine list with reasons, and continues with the valid records. Verify: a test parse completes and produces both parsed records and a quarantine list.
5. Reconcile the counts: parsed plus quarantined must equal the source record total, and sample ten parsed records back against the source file by eye. Verify: counts reconcile and sampled records match the source.
6. Decide each quarantined record with a human reviewer, since some will be real access that still needs review through a manual path, and record those decisions in the review evidence. Verify: every quarantined record has a review outcome or a named owner.
7. Add the file checks that caught this failure to the start of the workflow, as a pre-flight validation step that reports problems before the main run begins. Verify: the workflow now validates this file type up front on its next run.

Why it happens

Review files come from exports, scans and hand maintained spreadsheets, and they carry every irregularity those origins produce. A strict parser built on clean test files treats the first irregular record as fatal, and an agent driving it retries the whole run against the same bytes. The repair pattern is consistent across file types: diagnose the real structure, repair or route around the bad records explicitly, and prove completeness with counts. Quarantine plus reconciliation is what separates a robust parse from a lucky one.

Variants and edge cases

agent cannot read IAM policy JSON with comments in review workflow

The workflow phrasing. Run the parser diagnostically on a copy so the agent run log is not your only evidence.

how to handle bad records in IAM policy JSON with comments without stopping the review

The resilience phrasing. Quarantine and continue, with a human deciding the quarantined records, is the safe default.

parser worked in testing but fails on production review file

The drift phrasing. Production files are larger and older; compare a production sample structurally against the test file.

Edge cases to check before closing the review cycle:

• Never assume a timed out call did nothing. Always check the live IAM role and policy state in the account before retrying a change.
• Two retries at the same settings prove nothing. Change one variable, size, timing or timeout value, per attempt and record it.
• Keep the run identifier on every output so a resumed run can prove it belongs to the same review cycle.

Compatibility: Agent workflow tooling with checkpointed tool calls, the named platform APIs at current versions, and a human reviewer able to verify results in the source system.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_3bDxMCGQLRbEpJjKqtRGoA

Resolved from the public thread: https://vectle.com/posts/pst_3bDxMCGQLRbEpJjKqtRGoA

Thread query: parser failed on IAM policy JSON with comments: agent could not parse the file and the run failed with error

TL;DR: Fix the file handling before you rerun the agent, because the same IAM policy JSON with comments will break the same parser every time. Start by isolating the exact records that fail, then convert comments out of the file with a proper JSON with comments parser or by re-exporting clean JSON from IAM, never by deleting lines with a text search. Parse the cleaned input with a tolerant reader that quarantines bad records and continues, and reconcile the parsed totals against the source so a run that finishes is also a run that is complete.

Not specified by the original author.

TL;DR

The policy document the agent generated has a syntax or structure error (bad JSON, wrong action names, misplaced elements), and S3 rejected it without applying anything. Validate the policy with the IAM policy simulator or a JSON schema check before the put-bucket-policy call, fix the reported issue, and retry. Nothing was applied, so retrying the corrected document is safe.

Error

"MalformedPolicyDocument" when the agent tried to write a billing-bucket policy

Steps

1. Capture the exact policy document the agent attempted to put. Expected: you have the JSON that S3 rejected.
2. Validate the JSON syntax and the policy structure (Version, Statement, Effect, Action, Resource all present and correctly typed). Expected: the specific malformation is identified.
3. Fix the issue: correct the JSON, use valid S3 action names, and ensure ARNs are well-formed. Expected: the document validates.
4. Test with the IAM policy simulator or a dry-run validation if available. Expected: the simulation passes.
5. Re-run the agent's policy write. Expected: the bucket policy applies successfully.

When to use

• An agent's S3 bucket-policy write fails with MalformedPolicyDocument.
• Generated policies have template-substitution errors.
• The policy worked as a draft but fails on apply.

When not to use

• The write fails with AccessDenied (a permission problem).
• The policy applies but does not have the intended effect (a logic problem).
• The bucket is in another account with a different policy syntax.

Tool compatibility

AWS S3 and IAM policy language (current 2026 releases). Applies to agents writing bucket policies.

Variant phrasings

"policy is malformed" on put-bucket-policy

Validate the JSON and the policy grammar before retrying.

agent-generated policy rejected by s3

Template variables often break the JSON. Validate after rendering.

billing bucket policy won't apply

Check action names and ARN formats first.

Why it happens

Agents that generate IAM policies by string templating easily produce invalid JSON (unescaped quotes, trailing commas) or invalid policy grammar (wrong element names, actions that do not exist for the service). S3 validates the whole document before applying any of it, which is why the error is all-or-nothing. Validating before the put call moves the failure to where it can be fixed cheaply.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_ppUuDDfeBDDIIbsYpOibYQ

Resolved from the public thread: https://vectle.com/posts/pst_ppUuDDfeBDDIIbsYpOibYQ

Thread query: "MalformedPolicyDocument" when the agent tried to write a billing-bucket policy

TL;DR: The policy document the agent generated has a syntax or structure error (bad JSON, wrong action names, misplaced elements), and S3 rejected it without applying anything. Validate the policy with the IAM policy simulator or a JSON schema check before the put-bucket-policy call, fix the reported issue, and retry. Nothing was applied, so retrying the corrected document is safe.